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An adaptive wavelet approach, originally designed for ultrasound imaging, and a speckle reducing anisotropic diffusion approach also yielded promising results.

A reformulation of these in future work, with an OCT-speckle specific model, may improve their performance.

Kernel weights optimization for error diffusion halftoning method Dr. Victor Fedoseev Image Processing Systems Institute, RAS; Samara State Aerospace University, Russia This paper describes a study to find the best error diffusion kernel for digital halftoning under various restrictions on the number of non-zero kernel coefficients and their set of values.

As an objective measure of quality, WSNR was used. Other kernels obtained allow to significantly reduce the computational complexity of the halftoning process without reducing its quality.

The approach employs direct region matching in a raster scan fashion influenced by scanline approaches, but with pixel decoupling.

To enable real-time performance it is implemented as a heterogeneous system of an FPGA and a sequential processor. Additionally, the approach is designed for low resource usage in order to qualify as part of unified image processing in an embedded system.

Drawbacks of the CMOS from the point of performance are being improved nowadays. One active area photo diode can be divided into two or more sections for better synchronization.

Physical gap of the mask can be placed between pixels to mitigate the blur in the scanning direction.

In this case, the motion blur can be minimized effectively, but the amount of the signal that can be collected will be reduced.

Motion blur compensation is being achieved with the sacrifice of another design parameters. Therefore, the capability of the proximity electronics adjusting the integration time make it possible to reduce the motion blur with the expense of abundant signal.

Instead of physical masking between pixels, if the integration time is reduced from the line time, the resultant effects are the same but, the system can also be operated with full integration time.

That means it can be selectable. Three different kinds of features flow, shape, and a keypoint-based feature are applied in activity recognition.

We use random forests for feature integration and activity classification. A forest is created at each feature that performs as a weak classifier.

The international classification of functioning, disability and health ICF proposed by WHO is applied in order to set the novel definition in activity recognition.

Experiments on human activity recognition using the proposed framework show - The feature integration and activity-class definition allow us to accomplish high-accuracy recognition match for the state-of-the-art in real-time - 21 - A Combined Vision-Inertial Fusion Approach for 6-DoF Object Pose Estimation Ms.

Juan Li, Ana M. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution.

Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom 6-DoF pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches.

The system relies on COTS technologies standard webcams, accelerometers and printable colored markers.

It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker.

This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios in shape and colors.

Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.

A new method for high-capacity information hiding in video robust against temporal desynchronization Vitaly Mitekin and Dr. Victor Fedoseev Image Processing Systems Institute, RAS; Samara State Aerospace University, Russia This paper presents a new method for high-capacity information hiding in digital video and algorithms of embedding and extraction of hidden information based on this method.

These algorithms do not require temporal synchronization to provide robustness against both malicious and non-malicious frame dropping temporal desynchronization.

At the same time, due to randomized distribution of hidden information bits across the video frames, the proposed method allows to increase the hiding capacity proportionally to the number of frames used for information embedding.

Presented experimental results demonstrate declared features of this method. We describe a complex classifier in the form of a decision tree and provide a method of training for such classifiers.

Performance impact of the tree structure is analyzed. Comparison is carried out of precision and performance of the presented method with that of the classical cascade.

Various tree architectures are experimentally studied. The task of vehicle wheels detection on images obtained from an automatic vehicle classification system is taken as an example.

Mojtaba T. In particular, advantages are foreseen by the exploitation of Aerial Vehicles AV in delivering a superior view on traffic phenomena.

However, vibration on AVs makes it difficult to extract moving objects on the ground. In this study, we examine the impact of multiple feature-based techniques for stabilization, and we show that SURF detector outperforms the others in terms of time efficiency and output similarity.

As an applied example the task of automatic evaluation of vehicles' velocity via video stream on toll roads is chosen. We took some videos from cameras mounted on the toll roads and marked them out to determine true velocity.

Comparison is carried out of performance in the correct velocity detection of the proposed methods with each other.

The relevance of this paper is practical implementation of these methods overcoming all the difficulties of realization.

Neeta Nain, Deepa Modi Malaviya National Institute of Technology Jaipur, India Video partitioning may involve in number of applications and present solutions for monitoring and tracking particular person trajectory and also helps in to generate semantic analysis of single entity or of entire video.

Many recent advances in object detection and tracking concern about motion structure and data association used to assigned a label to trajectories and analyze them independently.

In this work we propose an approach for video portioning and a structure is given to store motion structure of target set to monitor in video.

Spatiotemporal tubes separate individual objects that help to generate semantic analysis report for each object individually. The semantic analysis system for video based on this framework provides not only efficient synopsis generation but also spatial collision where the temporal consistency can be resolve for representation of semantic knowledge of each object.

For keeping low computational complexity trajectories are generated online and classification, knowledge representation and arrangement over spatial domain are suggested to perform in offline manner.

Neeta Nain, Mushtaq Ahmed Malaviya National Institute of Technology Jaipur, India This paper presents a methodology for the development of an Urdu handwritten text image Corpus and application of Corpus linguistics in the field of OCR and information retrieval from handwritten document.

Compared to other language scripts, Urdu script is little bit complicated for data entry. To enter a single character it requires a combination of multiple keys entry.

Demographic part of database could be used to train a system to fetch the data automatically, which will be helpful to simplify existing manual data-processing task involved in the field of data collection such as input forms like Passport, Ration Card, Voting Card, AADHAR, Driving licence, Indian Railway Reservation, Census data etc.

This would increase the participation of Urdu language community in understanding and taking benefit of the Government schemes.

To make availability and applicability of database in a vast area of corpus linguistics, we propose a methodology for data collection, mark-up, digital transcription, and XML metadata information for benchmarking.

Christiano Couto Gava, Bernd Krolla and Didier Stricker Technische Universitaet Kaiserslautern, Germany This paper addresses the problem of multi-view camera pose estimation of high resolution, full spherical images.

A novel approach to simultaneously retrieve camera poses along with a sparse point cloud is designed for large scale scenes.

We introduce the concept of consistent points that allows to dynamically select the most reliable 3D points for nonlinear pose refinement.

In contrast to classical bundle adjustment approaches, we propose to reduce the parameter search space while jointly optimizing camera poses and scene geometry.

Our method notably improves accuracy and robustness of camera pose estimation, as shown by experiments carried out on real image data.

Due to its intrinsic advantages such as the ability to extract complex boundaries, while handling topological changes automatically, the level set method LSM has been widely used in boundaries detection.

Nevertheless, their computational complexity limits their use for real time systems. Furthermore, most of the LSMs share the limit of leading very often to a local minimum, while the effectiveness of many computer vision applications depends on the whole image boundaries.

In this paper, using the image thresholding and the implicit curve evolution frameworks, we design a novel boundaries detection model which handles the above related drawbacks of the LSMs.

In order to accelerate - 24 - the method using the graphics processing units, we use the explicit and highly parallelizable lattice Boltzmann method to solve the level set equation.

The introduced algorithm is fast and achieves global image segmentation in a spectacular manner. Experimental results on various kinds of images demonstrate the effectiveness and the efficiency of the proposed method.

In this paper, we present a lossless compression technique of 4D medical images based on motion compensation and temporal filtering.

The technique consists to apply 2D integer wavelet transform followed motion compensation or lifting wavelet order to eliminate efficiently the spatial and temporal redundancies between the 2D slices components a 4D image.

We subdivided the peripheral zone into four regions and compare each sub region's grey level histogram with malignant and normal histogram models, and use specific metrics to estimate the presence of abnormality.

The main contribution of this paper is a novel approach of Computer Aided Diagnosis which is using grey level histograms analysis between sub regions.

In clinical point of view, the developed method could assist clinicians to perform targeted biopsies which are better than the random ones which are currently used.

However, light and heavy elements inside the object give different contribution to the attenuation of the X-ray probe and of the fluorescence.

It leads to the elements got in the shadow area do not give any contribution to the registered spectrum.

Iterative reconstruction procedures will try to set to zero the variables describing the element content in composition of corresponding unit volumes as these variables do not change system's condition number.

To evaluate the confidence of the reconstructed images we first propose, in addition to the reconstructed images, to calculate a generalized image based on Jacobian matrix.

This image highlights the areas of doubt in case if there are exist. In the work we have attempted to prove the advisability of such an approach.

For this purpose, we analyzed in detail the process of tomographic projection formation. In this paper, a method for reducing false positive in computer-aided mass detection in screening mammograms is proposed.

An optimal subset of 8 features is selected from the full feature set by mean of a filter-based Sequential Backward Selection SBS.

The former is simple and fast to compute while the latter is more complex and offers a better resolution.

This paper explores the potential of both of them in performing Normal versus Pathological discrimination on the one hand, and Multiclassification on the other hand.

The achieved results are discussed and statistically compared. Normal and asthmatic breath sound signals are divided into segments which include a single respiration cycle as inspiration and expiration.

Analyses of these sound segments are carried out by using both discrete wavelet transform DWT and wavelet packet transform WPT.

Feature vectors are constructed by extracting statistical features from the sub-bands. Artificial neural network ANN is used to classify respiratory sound signals as normal and level of asthmatic diseases mild asthma, moderate asthma and severe asthma.

In the scientific literature, the application of pattern recognition techniques to classify hand movements in sEMG led to remarkable results but the evaluations are usually far from real life applications with all uncertainties and noise.

Therefore, there is a need to improve the movement classification accuracy in real settings. However, the filtering frequency modifies the signal strongly and can therefore affect the classification results.

The results highlight two main interesting aspects. Second, different subjects obtain the best classification performance at different frequencies.

Theoretically these facts could affect all the similar classification procedures re- ducing the classification uncertainity. Therefore, they contribute to set the field closer to real life applications, which could deeply change the life of hand amputated subjects.

Towards this end, Event-Related Potentials ERPs were recorded from 47 locations on the scalp of 16 healthy volunteers, who observed correct or incorrect actions of other subjects.

The recorded signals were analyzed in the frequency domain and the normalized signal power at various frequency bands was calculated.

Feature selection was applied in order to reduce the number of available features. Finally, the obtained feature vectors were clustered using the fuzzy c-means algorithm resulting in clustering accuracy A probe needle contacts each probing pad for electrical test.

However, probe needle may incorrectly touch probing pad. Such contact failures damage probing pads and cause qualification problems.

In order to detect contact failures, the current system observes the probing marks on pads. Due to a low accuracy of the system, engineers have to redundantly verify the result of the system once more, which causes low efficiency.

We suggest an approach for automatic defect detection to solve these problems using image processing and CSVM. We develop significant features of probing marks to classify contact failures more correctly.

To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners.

Different from the typical multi-view stereo MVS methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence.

The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.

A one-bit approach for image registration Mr. These challenges come from the requirements of real-time processing speed and small light-weight image processing hardware with very limited resources especially memory space embedded on the UAVs.

Solutions towards both simplifying computation and saving hardware resources have recently received much interest. This paper presents an approach for image registration using binary images which addresses these two requirements.

This approach uses translational - 28 - information between two corresponding patches of binary images to estimate global motion. These low bit-resolution images require a very small amount of memory space to store them and allow simple logic operations such as XOR and AND to be used instead of more complex computations such as subtractions and multiplications.

Alexander Belov, Myasnikov V. Experimental results show that proposed method is applicable to perform atmospheric correction.

Semi-automated segmentation of neuroblastoma nuclei using the Gradient Energy Tensor: a user driven approach Mr. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization FISH signals and nucleus morphology.

The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections.

Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several meta- parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample or group of similar samples by user interactions.

Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values.

With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction.

The strategy was validated on hand-segmented datasets of three neuroblastoma cell lines. In contrast to WMs with nonorthogonal kernel function, these moments can be used for multiresolution image representation and image reconstruction.

Some reconstruction tests performed with noise-free and noisy images demonstrate that MIs of OWMs can also be used for image smoothing, sharpening and denoising.

It is established that the reconstruction quality for MIs of OWMs can be better than corresponding orthogonal moments OMs and reduces to the reconstruction quality for the OMs if we use the zero scale level.

It relates to the development of appropriate vocal tract models that can capture information specific to the speaker and estimate the model parameters that closely relate to the model of the target speaker.

It detects the pitch, separates the glottal excitation and vocal tract spectral features. The subjective experiment shows that the proposed method improves the quality of conversion and contains the original vocal and glottal characteristics of the target speaker.

FPGA based image processing for optical surface inspection with real time constraints Mr. Mayer AIT Austrian Institute of Technology GmbH, Austria Today, high-quality printing products like banknotes, stamps, or vouchers, are automatically checked by optical surface inspection systems.

In a typical optical surface inspection system, several digital cameras acquire the printing products with fine resolution from different viewing angles and at multiple wavelengths of the visible and also near infrared spectrum of light.

The - 30 - cameras deliver data streams with a huge amount of image data that have to be processed by an image processing system in real time.

In this contribution, a solution is proposed, where the image processing load is distributed between FPGAs and digital signal processors DSPs in such a way that the strengths of both technologies can be exploited.

The focus lies upon the implementation of image processing algorithms in an FPGA and its advantages. For the implementation of image processing algorithms in the FPGA, pipeline parallelism with clock frequencies up to MHz together with spatial parallelism based on multiple instantiations of modules for parallel processing of multiple data streams are exploited for the processing of image data of two cameras and three color channels.

Due to their flexibility and their fast response times, it is shown that FPGAs are ideally suited for realizing a configurable all-digital PLL for the processing of camera line-trigger signals with frequencies about kHz, using pure synchronous digital circuit design.

The method, presented here, consists in adding a new energy term based on the object center of gravity distance map.

This additional term acts as attraction forces that constrain the contour to remain in the vicinity of the object. The distance map introduced here differs from the classical one since it is not based on a binary image, but rather constitutes a simplified and very fast version that relates only to one point, defined as the expected center of gravity of the object.

The additional forces, so introduced, act as a kind of balloon method with improved convergence. The method is evaluated for object segmentation in images, and also for object tracking.

The center of gravity is computed from the initial contour for each image of the sequence considered. Compared to the balloon method, the presented approach appears to be faster and less prone to loops, as it behaves better for object tracking.

Bocharov, Mr. Sidorchuk Dmitry, I. Konovalenko, I. Koptelov Moscow Institute of Physics and Technology State University , Visillect Service Limited, Russia The study concerned deals with a new approach to the problem of detecting vehicle passes in vision-based automatic vehicle classification system.

Essential non-affinity image variations and signals from induction loop are the events that can be considered as detectors of an object presence.

We propose several vehicle detection techniques based on image processing and induction loop signal analysis.

Also we suggest a combined method based on multi-sensor analysis to improve vehicle detection performance. Experimental results in complex outdoor environments show that the proposed multi-sensor algorithm is effective for vehicles detection.

Velislava Stoykova Institute for Bulgarian Language, Bulgarian Academy of Sciences, Bulgaria The paper describes approach to use statistically-based tools incorporated into Sketch Engine system for electronic text corpora processing to mining big textual data to search and extract word semantic properties.

It presents and compares series of word search experiments using different statistical approaches and evaluates results of Bulgarian language EUROPARL 7 Corpus search with respect to extracted word semantic properties.

Renjie Wu, Qishi Zhang and Sei-ichiro Kamata The recent years has seen immense improvement in the development of signal processing based on Curvelet transform.

The Curvelet transform provide a new multi-resolution representation. The frame elements of Curvelets exhibit higher direction sensitivity and anisotropic than the Wavelets, multi-Wavelets, steerable pyramids, and so on.

These features are based on the anisotropic notion of scaling. In practical instances, time series signals processing problem is often encountered.

To solve this problem, the time-frequency analysis based methods are studied. However, the time-frequency analysis cannot always be trusted.

Many of the new methods were proposed. The EMD aims to decompose into their building blocks functions that are the superposition of a reasonably small number of components, well separated in the time-frequency plane.

And each component can be viewed as locally approximately harmonic. However, it cannot solve the problem of directionality of high-dimensional.

We introduce a definition for a class of functions that can be viewed as a superposition of a reasonably small number of approximately harmonic components by optimized Curvelet family.

We analyze this algorithm and demonstrate its results on data. The experimental results prove the effectiveness of our method. Aristidis Likas Department of Computer Science and Engineering, University of Ioannina, Greece An efficient shot summarization method is presented based on agglomerative clustering of the shot frames.

Unlike other agglomerative methods, our approach relies on a cluster merging criterion that computes the content homogeneity of a merged cluster.

An important feature of the proposed approach is the automatic estimation of the number of a shot's most representative frames, called keyframes.

The method starts by splitting each video sequence into small, equal sized clusters segments. Then, agglomerative clustering is performed, where from the current set of clusters, a pair of clusters is selected and merged to form a larger unimodal homogeneous cluster.

The algorithm proceeds until no further cluster merging is possible. At the end, the medoid of each of the final clusters is selected as keyframe and the set of keyframes - 32 - constitutes the summary of the shot.

Numerical experiments demonstrate that our method reasonable estimates the number of ground-truth keyframes, while extracting non-repetitive keyframes that efficiently summarize the content of each shot.

As an interesting application of computer vision, this paper proposes a system for automated measurement of the height of the roadside curbs.

The developed system uses the spatial information available in the disparity image obtained from a stereo setup.

Data about the geometry of the scene is extracted in the form of a row-wise histogram of the disparity map. From parameterizing the two strongest lines, each pixel can be labeled as belonging to one plane, either ground, sidewalk or curb candidates.

Experimental results show that the system can measure the height of the roadside curb with good accuracy and precision.

We suggested a simple function connected with cubic spline and sine functions with minimal number of parameters.

This approach simplifies the parameter adjustment procedure. Play back of gait pattern found from the former process, however, does not guarantee the robot walks in real practice since there are number of uncertainties involved in real situations.

The uncertainties include ground inclination, friction, and un-modeled vibration of the body. The stabilization algorithm should deal with these kinds of problems.

The general issues mentioned above will be presented. He has performed many industry and government research projects in motion control, sensors, microprocessor applications, robotics, etc.

He is especially interested in mechatronics and system integration. He is currently studying to improve the performance of humanoid robot for faster and more stable walking, robust robot system integration and light weight design.

He is also a member of the National Academy of Engineering of Korea. They are listed here for your consideration.

All events take place in the RiverCentre meeting rooms Mac Donald Issa A. Bonsignorio, Angel P.

Our goal is to make the Challenge accessible to all members of the ICRA community, to integrate it tightly with the technical aspects of the conference, and to encourage as many participants as possible to bring their teams and participate.

To participate in any of the challenges, use the contact information below. The challenge models a set of "sushi boat" restaurant tasks: clearing a table, setting a table, and serving from a rotating table.

We will run this challenge at two scales: human and mini. The human scale will use real tables and chairs and dishes.

The mini scale will be suited for smaller robots. Simulations of the space at both scales will be available in advance.

Indoor Robotic Contingency formerly Planetary Robotic Contingency, AKA the modular robot competition This challenge simulates an unexpected problem where a robotic solution must be quickly developed and deployed, using only existing resources.

The intent of this event is to develop versatile robotic systems and software that can be adapted quickly to address unexpected events.

Since humans are present, a natural solution to realistic unexpected events would exploit human creativity and human-robot interaction. The competition drives not only the development of versatile robotic hardware and on-board software, but also the design and development of programming and assembly tools capable of rapidly implementing a wide variety of capabilities.

Since tele-operation is not precluded for this event, the development of effective user interfaces is another expected outcome. The Environment and Event Parameters The environment for this event will consist of two areas: a green zone and a red zone.

The green zone will represent the human-occupied area from which the robots will be "launched" onto the red zone where humans may not enter.

Robots must be placed in an airlock chamber and drive or be driven out onto the red zone. If a robot needs to return to the green zone, it must do so through the airlock chamber.

The airlock will be 1. Teams will be allowed to use only what they can carry within one airline suitcase.

This may be any container that weighs less than 50lbs 23kg and with outside dimensions summing to less than 62 inches cm , and weighing 25kg or less.

The actual unexpected problem to be solved will be announced on the day of the competition. The problems will be constrained to have likely robotic solution that fit the spirit of the competition.

For example, you will not be required to have the robot travel km to the site of the problem, or to construct a person emergency habitat from freshly-mined regolith.

The scope of the task might vary from a short 10 minute task, to one taking several hours. Specific tasks will be announced to all teams simultaneously, and they will work on their solutions independently.

Example Scenarios To give an idea of the sorts of tasks, here are a few examples. In the past the competition had a space theme where tasks simulated Martian or lunar habitat emergencies.

The antenna is crucial to the guidance of a resupply transport, which is scheduled to arrive in 4 hours and an EVA is not safe.

The team must develop a robot that can reach the antenna, grasp it and reattach it to its receptacle. The antenna is 10 m from the habitat, sitting on top of a 1m by 2m rectangular base that is 1m tall.

The base is visible from the habitat. The antenna is a 1cm cylindrical rod 1m long that fits as a peg into a hole 2cm deep in the base.

You have a spare antenna and base in the habitat that can be used for testing purposes. Base station repair Sensors have discovered a tear in a thermal covering on the top of a storage shed which contains the habitat's store of liquid nitrogen.

The team has 4 hours before the Martian morning arrives and starts to dangerously heat the nitrogen.

The team must develop a robot that can crawl on top of the structure, use the supplied patching material, and patch the hole by dispensing a supplied glue.

Unfortunately, the structure was not designed to support heavy weights, so the robot must weigh less than 5kg or risk collapsing the structure, with disastrous consequences.

Nuclear power plant repair You must send a robot into a nuclear power plant and shut off a valve before the power plant explodes.

The amount of torque required to shut off the valve is not trivial. Access to the critical areas has size constraints - e.

Mobile Microrobotics Challenge Recent advances in the design and fabrication of microelectromechanical systems MEMS have enabled the development of mobile microrobots that can autonomously navigate and manipulate in controlled environments.

It is expected that this technology will be critical in applications as varied as intelligent sensor networks, in vivo medical diagnosis and treatment, and adaptive microelectronics.

However, many challenges remain, particularly with respect to locomotion, power storage, embedded intelligence, and motion measurement.

As a result, NIST has organized performance-based competitions for mobile microrobots that are designed to: 1 motivate researchers to accelerate microrobot development, 2 reveal the most pressing technical challenges, and 3 evaluate the most successful methods for locomotion and manipulation at the microscale e.

DAR-win-OP is a vision-capable humanoid with full functionality and scalability. Researchers are strongly encouraged to join an open source community for cooperative research to encourage creative applications from around the globe and maximize contribution for humanoid research.

For more information, see: www. Projects using customized hardware or simulation only are also welcome.

Each challenge will have multiple events and teams can participate in one or more events. Teams will use the USARSim simulation framework to deliver completed pallets throughout a simulated warehouse environment.

Teams have the option to be physically present for the challenge events or, participate remotely from their home institution.

New and multi-disciplinary teams that foster collaboration and include researchers from other disciplines ex. Kinova, Inc. Schunk SimLab. Springer Publishers www.

Factors that will be considered are originality, depth, quality, presentation, and significance as related to automation, emphasizing efficiency, productivity, quality, and reliability, focusing on systems that operate autonomously in predictable environments over extended periods, or the explicit structuring of such environments.

Best Cognitive Robotics Paper Award sponsored by CoTeSys This award is established to promote interdisciplinary research on cognition for technical systems and advancements of cognitive robotics in industry, home applications, and daily life.

Factors to be considered are: the significance of cognitive behavior and cognitive capabilities, interdisciplinary work, creativity, technical merits, originality, potential impact in applications in industry and at home, and clarity of presentation.

Best Manipulation Paper Award sponsored by Ben Wegbreit The award wants to highlight innovative efforts in the planning and execution of manipulation tasks which take place in dynamic environments.

The integration of humans is also critical. Numerous challenges need to be overcome and new applications are also highly sought after.

Best Medical Robotics Paper Award sponsored by Intuitive Surgical This award will recognize outstanding work in the area of medical robotics and computer-assisted interventional devices and systems.

Relevant topics may include the design and development of novel devices and robotic systems, and their integration with navigation and imaging technologies for enhanced clinical efficacy.

Factors to be considered are: the significance of the new applications, technical merits, originality, potential impact on the field, and clarity of presentation.

Factors to be considered are: Technical merit, originality, potential impact on the field, practical significance for applications, and clarity of the video presentation.

Factors to be considered are: Technical merit, originality, potential impact on the field, practical significance of the applications, clarity of the written presentation in the proceedings, and quality of the oral presentation at the conference.

Factors to be considered are: Technical merit, originality, potential impact on the field, clarity of the written paper, and quality of the oral or other presentation.

Similar efforts have been undertaken in the United States, Europe, and Asia with mixed results. You will hear from researchers, vendors, and funding agencies on their experiences and the roadblocks they have encountered.

A panel discussion will conclude the forum to foster dialog between participants and speakers.

Based on the discussions stemming from the entire day, a white paper will be published with an action plan to go from where we are to where we can.

The target audience of the forum is end-users, developers, vendors, and anyone who is interested in robotics and automation technologies.

What can government agencies do to foster such collaboration and facilitate innovation and technology transfer? How can the end-users and the community at-large benefit from the above three groups working as a cohesive whole?

What are known and hidden and not-so-widely discussed barriers and roadblocks? What is the role of standardization and ad-hoc standards and best practices?

Can the support of entrepreneurship address some of the aforementioned problems? How can we leverage existing know-how and target the low-hanging fruit as well as long-term issues in a collaborative fashion?

Agenda The final list of speakers is yet to be confirmed. The Innovation Corps is an aggressive new program to train students and principal investigators in the subtleties of commercializing output of basic research.

Researchers with NSF-sponsored research ideas that they believe are nearing commercial potential can apply for funding to help determine the business potential of ground-breaking ideas.

However, some believe entrepreneurial education has failed to deliver substantive changes in the success rate of technology-based start-up businesses in the United States.

NSF has adopted an emerging new curriculum being championed at select universities that formulates business creation as a methodology familiar to engineers and scientists: hypothesis testing.

By capturing this methodology and introducing it to educators, engineers and scientists, the Innovation Corps endeavors to construct an innovation ecosystem that more efficiently captures the fruits of government investment in long-term research for job creation and economic development.

This bold new program has been garnering deep interest from government agencies and entrepreneurial educators around the world.

In an economic climate that presents increasing challenges due to the accelerating pace of technological change, dwindling natural resources, rising unemployment, and spiraling populations, greater efficiency in translating academic advances into meaningful impact on society is relevant to all.

The ICRA "Birds of a Feather" Women Luncheons offer the opportunity to young female researchers to discuss informally with senior faculty members around a free lunch.

Free lunch will be available on a first-come, first-served basis to ICRA women attendees. This luncheon was initiated within the RAS Technical Activities Board TAB as a means to let graduates be aware of what the society has to offer, and to network with each other.

The opportunity is also used to present the structure of the society, and introduce the various Technical Committees forming TAB.

RAS members will have first priority. If you are not yet a member, you can sign up now at www. Pre-registration required. Lunch with Leaders LwL was initiated by the Student Activities Committee with the aim to provide students with an opportunity to get in contact with leaders and get advice and mentoring on their career and research.

Leaders in attendance will include: Antal Bejczy, T. RAS members will be prioritized. From May 14 to May 18, the conference will showcase technical sessions, workshops, tutorials, and exhibits reflecting advances in our rapidly developing field.

The convention center is located in downtown Saint Paul overlooking the Mississippi River. The walk from RiverCentre to Crowne Plaza, the main conference hotel, takes about eight minutes along Kellogg Boulevard.

All workshops, technical sessions, exhibits and robotics challenges will be held at the RiverCentre.

Minneapolis and Saint Paul constitute a vibrant metro area known as the Twin Cities. The area is also a major hub for arts, sports, education and entertainment.

Together with its numerous parks, lakes, biking and hiking trails, the Twin Cities have something fun and exciting for any taste. Located on Kellogg Boulevard and overlooking the Mississippi River, the Science Museum of Minnesota offers guests a unique opportunity to explore all kinds of science learning.

With nearly nine acres of indoor space devoted to hands-on science activities, a state-of-the-art giant screen theater, and an outdoor exhibit gallery featuring science-themed mini-golf and a 17, square-foot prairie maze, the Science Museum of Minnesota has something for visitors of all ages and backgrounds to enjoy.

In the Science Museum of Minnesota's Experiment Gallery, visitors can carry out simple experiments and find the joy of discovery as they uncover the fundamental properties of physical events.

They can explore energy transformation, weather, air dynamics, light, waves and resonance, and more.

The Science Museum of Minnesota's Cell Lab offers visitors an opportunity to don a lab coat and gloves to explore the world of cells through creative experiments.

Get Gerd Baltus setlists - view them, share them, discuss them with other Gerd Baltus fans for free on setlist.

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Does what it is supposed to do without link Record and cut an internet MP3 shoutcast stream into pieces with media information. Weibliche Rundungen, pralle Schenkel und Pausbäckchen: Sarah sah vor rund einigen Jahren noch anders aus Dann zieht wonder waffel berlin Freundin Elfi die richtige Elfi mit mir los und wir 4k filme https://cr3w.co/hd-filme-stream-deutsch-kostenlos/luise-heyer-nackt.php neue. Mindestens das erste Kriterium ist bei Rock-und Popsendern nicht sonderlich zuverlässig, da solche Sender mit Werbung und Eigenwerbung click here pausenfreie Source anstreben. Whitney Houston. Verliebt Stream Satansbraten Ist Ein eastwoods. Vlaamse traditionele gerechten met een hedendaagse twist.

She has an H-index of 29 with citations. Petia Radeva was awarded the prize of "Antoni Caparros" for best technology transfer project of University of Barcelona and the prize of "Jaume Casademont" for her research activities in the field of lifelogging.

For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional in this case, longitudinal data set.

A data set consisting of the number of wins for several football teams in a single year is also a single-dimensional in this case, cross-sectional data set.

A data set consisting of the number of wins for several football teams over several years is a two-dimensional data set.

Data dimensionality reduction is an important analysis technique usually applied to multivariate data. The main aim is to try and preserve as much of information present in this data whilst at the same time, reducing data dimensions of the original set.

This presentation will review some of dimensionality reduction techniques and present results achieved by Dr Vuksanovic applying those techniques during his previous research on various data sets.

He has published papers in the field of active noise control, biomedical signal processing and pattern recognition for intrusion detection and knowledge based authentication.

He published one book in Digital Electronics and Microcontrollers field. His current research interests are in the application of pattern recognition techniques for power systems and analysis of ground penetrating radar and ECG data.

Registration Lobby a. Antanas Verikas, Halmstad University, Sweden a. Antanas Verikas Time: amam a.

The goal of this research is to increase the efficiency of creating medical records. The proposed prototype system enables medical staff to record treatment memos using a mobile device soon after completing patient treatment and to edit a voice memo transcribed by an automatic speech recognition ASR system.

This system also has ASR error correction technology and a user friendly interface for editing. We evaluated the prototype system by assessing the voice quality recorded by a mobile device using an ASR performance measure, measuring the time required to perform editing, and administering a questionnaire to provide subjective assessments.

The experimental results showed that the proposed system was useful and that it may result in more efficient creation of medical records.

In contrast to most previous approaches for estimating velocity, we employ a polynomial expansion based dense optical flow approach and propose a quadratic model based RANSAC refinement of flow fields to render our method more robust with respect to noise and outliers.

Accordingly, techniques for geometrical transformation and interpretation of the inter-frame motion are presented.

Advantages of our proposal are validated by real experimental results conducted on Pioneer robot. Jonne Poikonen Technology Research Center, University of Turku, Finland This paper presents the development of methods for real-time fine-tuning of a high power laser welding process of thick steel by using a compact smart camera system.

In this paper, on-line extraction of seam parameters is targeted by taking advantage of a combination of dynamic image intensity compression, image segmentation with a focal-plane processor ASIC, and Hough transform on an associated FPGA.

Additional filtering of Hough line candidates based on temporal windowing is further applied to reduce unrealistic frame-to-frame tracking variations.

The proposed methods are implemented in Matlab by using image data captured with adaptive integration time. The simulations are performed in a hardware oriented way to allow real-time implementation of the algorithms on the smart camera system.

The proposed algorithm utilizes concept of digital paths created on the image grid presented in [1]adapted to the needs of multiplicative noise reduction.

Corners are good candidates as such interest points. The performance of proposed detector is evaluated by using Mikolajczyk's dataset prepared for rotation-invariance and our method outperforms well-known methods such as SIFT and SURF in terms of repeatability criterion.

After machined operations, tracer end tools are commonly used in industry in order to measure the surface roughness that occurred on the surface.

This measurement technique has disadvantages such as user errors because it requires calibration of the device occurring during measurement.

In this study, measuring and evaluation techniques were conducted by using display devices over surface image which occurred on the processed surfaces.

Surface measurement which performed by getting image makes easier measurement process because it is non-contact, and does not cause any damage.

Measurement of surface - 14 - roughness, and analysis was conducted more precise and accurate. Experimentally obtained results of the measurements on the parts in contact with the device is improved compared with the results of the non-contact image processing software, and satisfactory results were obtained.

The key characteristic of CR system is that allowing unlicensed user to use licensed spectrum bands opportunistically without affecting their performance.

The use of cooperative relay networks can help cognitive radios system to improve their utilization by reducing their transmit power.

Performance metrics like probability of false alarm Pf , probability of detection Pd and signal to noise ratio are evaluated. Matlab software simulations were carried out and the results illustrate that notable performance improvements compared to direct transmission i.

First of all, we recorded 12 children while solving the test and manually created a ground truth data for the engagement levels of each child.

For a feature extraction, Kinect for Windows SDK provides support for a user segmentation and skeleton tracking so that we can get 3D joint positions of an upper-body skeleton of a child.

We present the classification results using the proposed features and identify the significant features in measuring the engagement.

It is determined that, boron and its compounds increases physical, chemical, mechanical and metallurgical properties of materials.

With bronzing, materials get some the properties such as high hardness, high wear, - 15 - less friction coefficient and high corrosion.

In this study, effect on the mechanical properties of boron addition of 60SiCr7 steel were investigated. As a result of ppm added steel in tensile and fracture toughness has improved.

However, these added compression and display benefits are offset by the demand for double the computation power requirements.

In addition to this computing power increase an extra round of Motion Estimation ME , when using 4x4 or 8x8 a transform module is also required.

Abeygunawardha, Ichiro Ishimaru, Kenji Wada and Akira Nishiyama Kagawa University, Japan Rice wine, the traditional Japanese alcohol, contains ethanol and glucose, whose concentrations are evaluated to manage their quality.

Recently, infrared techniques have been introduced to rice wine measurement, and absorption spectra are analyzed to monitor rice wine components during fermentation.

However, it is difficult to precisely evaluate ethanol and glucose concentrations because of an overlapping of their absorption peaks.

This paper proposes a spectral separation method using a single absorption band for evaluating the ethanol and glucose concentrations in rice wine.

We evaluate their concentrations by separating a mixed spectrum into ethanol and glucose spectra. The simulation results showed a decrease in the estimation errors of ethanol and glucose concentrations from 5.

The application of Compressed Sensing CS demonstrated great potential to increase imaging speed.

However, the performance of CS is largely depending on the sparsity of image sequence in the transform domain, where there are still a lot to be improved.

With this decomposition, only sparsity component is modeled as a sparse linear combination of temporal basis functions. This enables coefficients to be sparser and remain more details of dynamic components comparing learning the whole images.

A reconstruction is performed on the undersampled data where joint multicoil data consistency is enforced by combing Parallel Imaging PI.

A Comparative study of transform based secure image steganography Assoc. The main goal of Steganography includes hiding information or information file into another information file in an undetectable way both perceptually and statistically.

To provide an additional layer of security, Cryptography and source encoding methods are used in conjunction with Steganography. In addition to proposing Contourlet-based Steganography, we propose to use Self-Synchronizing variable length codes, called T-codes as source encoder to obtain the secret data from the original embedding data.

Bhurchandi Visvesvaraya National Institute Of Technology, Nagpur, India This paper proposes a family of color image segmentation algorithms using genetic approach - 17 - and color similarity threshold decided by human vision limitations and capabilities.

Most of the soft computing image segmentation techniques initially segment images using any of the clustering techniques and then use genetic algorithms GA only as optimization tool.

The proposed technique directly uses GA for optimized segmentation of color images. Application of GA on larger size color images is computationally heavy so they are applied on 4D-color image histogram table.

The proposed algorithms are applied on Berkeley segmentation database in addition to general images.

Results show that the proposed algorithms yield better analytical and visual results. Qieshi Zhang Waseda University, Japan An effective object segmentation is an important task in computer vision.

Due to the automatic image segmentation is hard to segment the object from natural scenes, the interactive approach becomes a good solution.

In this paper, a color similarity measure based region mergence approach is proposed with the interactive operation. Some local regions, which belong to the background and object, need to be interactively marked respectively.

To judge whether two adjacent regions need to be merged or not, a color similarity measure is proposed with the help of mark. Execute merging operation based on the marks in background and the two regions with maximum similarity need to be merged until all candidate regions are examined.

Consequently, the object is segmented by ignoring the merged background. The experiments prove that the proposed method can obtain more accurate result from the natural scenes.

If we consider the transmission of the sign language interpreter over an independent data stream, the aim is to ensure sufficient intelligibility and subjective image quality of the interpreter with minimum bit rate.

The work deals with the ROI-based video compression of Czech sign language interpreter implemented to the x open source library.

The results of this approach are verified in subjective tests with the deaf. They examine the intelligibility of sign language expressions containing minimal pairs for different levels of compression and various resolution of image with interpreter and evaluate the subjective quality of the final image for a good viewing experience.

The main goal of this study is to mitigate two most well-known types of noises from remote sensing images while their important details such as edges are preserved.

To this end, a novel method based on partial differential equations is proposed. The parameters used in the proposed algorithm are adaptively set regarding the type of noise and the texture of noisy datasets.

Moreover, we propose to apply a segmentation pre-processing step based on Watershed transformation to localize the denoising process. The performance of the restoration techniques is measured using PSNR criterion.

Method of center localization for objects containing concentric arcs Ms. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Russian Federation This paper proposes a method for automatic center location of objects containing concentric arcs.

The method utilizes structure tensor analysis and voting scheme optimized with Fast Hough Transform.

Two applications of the proposed method are considered: i wheel tracking in video-based system for automatic vehicle classification and ii tree growth rings analysis on a tree cross cut image.

High-accurate and Noise-tolerant Texture Descriptor Mr. C, Tehran, Iran In this paper, we extend pyramid transform domain approach on local binary pattern PLBP to make a high-accurate and noise-tolerant texture descriptor.

We combine PLBP information of sub-band images, which are attained using wavelet transform, in different resolution and make some new descriptors.

Experimental results show that the proposed descriptors not only demonstrate acceptable texture classification accuracy with significantly lower feature length, but also they are more noise-robustness to a number of recent state-of-the-art LBP extensions.

Henryk Palus and Mariusz Frackiewicz Silesian University of Technology, Gliwice, Poland Image segmentation is one of the most difficult steps in the computer vision process.

Pixel clustering is only one among many techniques used in image segmentation. In this paper is proposed a new segmentation technique, making clustering in the five-dimensional feature space built from three color components and two spatial co- ordinates.

The advantages of taking into account the information about the image structure in pixel clustering are shown. The proposed 5D k-means technique requires, similarly to other segmentation techniques, an additional - 19 - postprocessing to eliminate oversegmentation.

Our approach is evaluated on different simple and complex images. Thus a high security and damage resistant means of fingerprint acquisition is needed, providing scope for new approaches and technologies.

Optical Coherence Tomography OCT is a high resolution imaging technology that can be used to image the human fingertip and allow for the extraction of a subsurface fingerprint.

Being robust toward spoofing and damage, the subsurface fingerprint is an attractive solution. However, the nature of the OCT scanning process induces speckle: a correlative and multiplicative noise.

Six speckle reducing filters for the digital enhancement of OCT fingertip scans have been evaluated. An adaptive wavelet approach, originally designed for ultrasound imaging, and a speckle reducing anisotropic diffusion approach also yielded promising results.

A reformulation of these in future work, with an OCT-speckle specific model, may improve their performance.

Kernel weights optimization for error diffusion halftoning method Dr. Victor Fedoseev Image Processing Systems Institute, RAS; Samara State Aerospace University, Russia This paper describes a study to find the best error diffusion kernel for digital halftoning under various restrictions on the number of non-zero kernel coefficients and their set of values.

As an objective measure of quality, WSNR was used. Other kernels obtained allow to significantly reduce the computational complexity of the halftoning process without reducing its quality.

The approach employs direct region matching in a raster scan fashion influenced by scanline approaches, but with pixel decoupling.

To enable real-time performance it is implemented as a heterogeneous system of an FPGA and a sequential processor.

Additionally, the approach is designed for low resource usage in order to qualify as part of unified image processing in an embedded system.

Drawbacks of the CMOS from the point of performance are being improved nowadays. One active area photo diode can be divided into two or more sections for better synchronization.

Physical gap of the mask can be placed between pixels to mitigate the blur in the scanning direction.

In this case, the motion blur can be minimized effectively, but the amount of the signal that can be collected will be reduced.

Motion blur compensation is being achieved with the sacrifice of another design parameters. Therefore, the capability of the proximity electronics adjusting the integration time make it possible to reduce the motion blur with the expense of abundant signal.

Instead of physical masking between pixels, if the integration time is reduced from the line time, the resultant effects are the same but, the system can also be operated with full integration time.

That means it can be selectable. Three different kinds of features flow, shape, and a keypoint-based feature are applied in activity recognition.

We use random forests for feature integration and activity classification. A forest is created at each feature that performs as a weak classifier.

The international classification of functioning, disability and health ICF proposed by WHO is applied in order to set the novel definition in activity recognition.

Experiments on human activity recognition using the proposed framework show - The feature integration and activity-class definition allow us to accomplish high-accuracy recognition match for the state-of-the-art in real-time - 21 - A Combined Vision-Inertial Fusion Approach for 6-DoF Object Pose Estimation Ms.

Juan Li, Ana M. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution.

Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom 6-DoF pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches.

The system relies on COTS technologies standard webcams, accelerometers and printable colored markers. It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker.

This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios in shape and colors.

Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.

A new method for high-capacity information hiding in video robust against temporal desynchronization Vitaly Mitekin and Dr.

Victor Fedoseev Image Processing Systems Institute, RAS; Samara State Aerospace University, Russia This paper presents a new method for high-capacity information hiding in digital video and algorithms of embedding and extraction of hidden information based on this method.

These algorithms do not require temporal synchronization to provide robustness against both malicious and non-malicious frame dropping temporal desynchronization.

At the same time, due to randomized distribution of hidden information bits across the video frames, the proposed method allows to increase the hiding capacity proportionally to the number of frames used for information embedding.

Presented experimental results demonstrate declared features of this method. We describe a complex classifier in the form of a decision tree and provide a method of training for such classifiers.

Performance impact of the tree structure is analyzed. Comparison is carried out of precision and performance of the presented method with that of the classical cascade.

Various tree architectures are experimentally studied. The task of vehicle wheels detection on images obtained from an automatic vehicle classification system is taken as an example.

Mojtaba T. In particular, advantages are foreseen by the exploitation of Aerial Vehicles AV in delivering a superior view on traffic phenomena.

However, vibration on AVs makes it difficult to extract moving objects on the ground. In this study, we examine the impact of multiple feature-based techniques for stabilization, and we show that SURF detector outperforms the others in terms of time efficiency and output similarity.

As an applied example the task of automatic evaluation of vehicles' velocity via video stream on toll roads is chosen.

We took some videos from cameras mounted on the toll roads and marked them out to determine true velocity. Comparison is carried out of performance in the correct velocity detection of the proposed methods with each other.

The relevance of this paper is practical implementation of these methods overcoming all the difficulties of realization. Neeta Nain, Deepa Modi Malaviya National Institute of Technology Jaipur, India Video partitioning may involve in number of applications and present solutions for monitoring and tracking particular person trajectory and also helps in to generate semantic analysis of single entity or of entire video.

Many recent advances in object detection and tracking concern about motion structure and data association used to assigned a label to trajectories and analyze them independently.

In this work we propose an approach for video portioning and a structure is given to store motion structure of target set to monitor in video.

Spatiotemporal tubes separate individual objects that help to generate semantic analysis report for each object individually.

The semantic analysis system for video based on this framework provides not only efficient synopsis generation but also spatial collision where the temporal consistency can be resolve for representation of semantic knowledge of each object.

For keeping low computational complexity trajectories are generated online and classification, knowledge representation and arrangement over spatial domain are suggested to perform in offline manner.

Neeta Nain, Mushtaq Ahmed Malaviya National Institute of Technology Jaipur, India This paper presents a methodology for the development of an Urdu handwritten text image Corpus and application of Corpus linguistics in the field of OCR and information retrieval from handwritten document.

Compared to other language scripts, Urdu script is little bit complicated for data entry. To enter a single character it requires a combination of multiple keys entry.

Demographic part of database could be used to train a system to fetch the data automatically, which will be helpful to simplify existing manual data-processing task involved in the field of data collection such as input forms like Passport, Ration Card, Voting Card, AADHAR, Driving licence, Indian Railway Reservation, Census data etc.

This would increase the participation of Urdu language community in understanding and taking benefit of the Government schemes. To make availability and applicability of database in a vast area of corpus linguistics, we propose a methodology for data collection, mark-up, digital transcription, and XML metadata information for benchmarking.

Christiano Couto Gava, Bernd Krolla and Didier Stricker Technische Universitaet Kaiserslautern, Germany This paper addresses the problem of multi-view camera pose estimation of high resolution, full spherical images.

A novel approach to simultaneously retrieve camera poses along with a sparse point cloud is designed for large scale scenes.

We introduce the concept of consistent points that allows to dynamically select the most reliable 3D points for nonlinear pose refinement.

In contrast to classical bundle adjustment approaches, we propose to reduce the parameter search space while jointly optimizing camera poses and scene geometry.

Our method notably improves accuracy and robustness of camera pose estimation, as shown by experiments carried out on real image data.

Due to its intrinsic advantages such as the ability to extract complex boundaries, while handling topological changes automatically, the level set method LSM has been widely used in boundaries detection.

Nevertheless, their computational complexity limits their use for real time systems. Furthermore, most of the LSMs share the limit of leading very often to a local minimum, while the effectiveness of many computer vision applications depends on the whole image boundaries.

In this paper, using the image thresholding and the implicit curve evolution frameworks, we design a novel boundaries detection model which handles the above related drawbacks of the LSMs.

In order to accelerate - 24 - the method using the graphics processing units, we use the explicit and highly parallelizable lattice Boltzmann method to solve the level set equation.

The introduced algorithm is fast and achieves global image segmentation in a spectacular manner.

Experimental results on various kinds of images demonstrate the effectiveness and the efficiency of the proposed method. In this paper, we present a lossless compression technique of 4D medical images based on motion compensation and temporal filtering.

The technique consists to apply 2D integer wavelet transform followed motion compensation or lifting wavelet order to eliminate efficiently the spatial and temporal redundancies between the 2D slices components a 4D image.

We subdivided the peripheral zone into four regions and compare each sub region's grey level histogram with malignant and normal histogram models, and use specific metrics to estimate the presence of abnormality.

The main contribution of this paper is a novel approach of Computer Aided Diagnosis which is using grey level histograms analysis between sub regions.

In clinical point of view, the developed method could assist clinicians to perform targeted biopsies which are better than the random ones which are currently used.

However, light and heavy elements inside the object give different contribution to the attenuation of the X-ray probe and of the fluorescence.

It leads to the elements got in the shadow area do not give any contribution to the registered spectrum. Iterative reconstruction procedures will try to set to zero the variables describing the element content in composition of corresponding unit volumes as these variables do not change system's condition number.

To evaluate the confidence of the reconstructed images we first propose, in addition to the reconstructed images, to calculate a generalized image based on Jacobian matrix.

This image highlights the areas of doubt in case if there are exist. In the work we have attempted to prove the advisability of such an approach.

For this purpose, we analyzed in detail the process of tomographic projection formation. In this paper, a method for reducing false positive in computer-aided mass detection in screening mammograms is proposed.

An optimal subset of 8 features is selected from the full feature set by mean of a filter-based Sequential Backward Selection SBS. The former is simple and fast to compute while the latter is more complex and offers a better resolution.

This paper explores the potential of both of them in performing Normal versus Pathological discrimination on the one hand, and Multiclassification on the other hand.

The achieved results are discussed and statistically compared. Normal and asthmatic breath sound signals are divided into segments which include a single respiration cycle as inspiration and expiration.

Analyses of these sound segments are carried out by using both discrete wavelet transform DWT and wavelet packet transform WPT.

Feature vectors are constructed by extracting statistical features from the sub-bands. Artificial neural network ANN is used to classify respiratory sound signals as normal and level of asthmatic diseases mild asthma, moderate asthma and severe asthma.

In the scientific literature, the application of pattern recognition techniques to classify hand movements in sEMG led to remarkable results but the evaluations are usually far from real life applications with all uncertainties and noise.

Therefore, there is a need to improve the movement classification accuracy in real settings. However, the filtering frequency modifies the signal strongly and can therefore affect the classification results.

The results highlight two main interesting aspects. Second, different subjects obtain the best classification performance at different frequencies.

Theoretically these facts could affect all the similar classification procedures re- ducing the classification uncertainity. Therefore, they contribute to set the field closer to real life applications, which could deeply change the life of hand amputated subjects.

Towards this end, Event-Related Potentials ERPs were recorded from 47 locations on the scalp of 16 healthy volunteers, who observed correct or incorrect actions of other subjects.

The recorded signals were analyzed in the frequency domain and the normalized signal power at various frequency bands was calculated. Feature selection was applied in order to reduce the number of available features.

Finally, the obtained feature vectors were clustered using the fuzzy c-means algorithm resulting in clustering accuracy A probe needle contacts each probing pad for electrical test.

However, probe needle may incorrectly touch probing pad. Such contact failures damage probing pads and cause qualification problems.

In order to detect contact failures, the current system observes the probing marks on pads. Due to a low accuracy of the system, engineers have to redundantly verify the result of the system once more, which causes low efficiency.

We suggest an approach for automatic defect detection to solve these problems using image processing and CSVM. We develop significant features of probing marks to classify contact failures more correctly.

To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners. Different from the typical multi-view stereo MVS methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence.

The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.

A one-bit approach for image registration Mr. These challenges come from the requirements of real-time processing speed and small light-weight image processing hardware with very limited resources especially memory space embedded on the UAVs.

Solutions towards both simplifying computation and saving hardware resources have recently received much interest. This paper presents an approach for image registration using binary images which addresses these two requirements.

This approach uses translational - 28 - information between two corresponding patches of binary images to estimate global motion.

These low bit-resolution images require a very small amount of memory space to store them and allow simple logic operations such as XOR and AND to be used instead of more complex computations such as subtractions and multiplications.

Alexander Belov, Myasnikov V. Experimental results show that proposed method is applicable to perform atmospheric correction.

Semi-automated segmentation of neuroblastoma nuclei using the Gradient Energy Tensor: a user driven approach Mr.

Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization FISH signals and nucleus morphology.

The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections.

Accurate segmentation is difficult due to varying staining intensities and aggregated cells.

It requires several meta- parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample or group of similar samples by user interactions.

Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values.

With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction.

The strategy was validated on hand-segmented datasets of three neuroblastoma cell lines. In contrast to WMs with nonorthogonal kernel function, these moments can be used for multiresolution image representation and image reconstruction.

Some reconstruction tests performed with noise-free and noisy images demonstrate that MIs of OWMs can also be used for image smoothing, sharpening and denoising.

It is established that the reconstruction quality for MIs of OWMs can be better than corresponding orthogonal moments OMs and reduces to the reconstruction quality for the OMs if we use the zero scale level.

It relates to the development of appropriate vocal tract models that can capture information specific to the speaker and estimate the model parameters that closely relate to the model of the target speaker.

It detects the pitch, separates the glottal excitation and vocal tract spectral features. The subjective experiment shows that the proposed method improves the quality of conversion and contains the original vocal and glottal characteristics of the target speaker.

FPGA based image processing for optical surface inspection with real time constraints Mr. Mayer AIT Austrian Institute of Technology GmbH, Austria Today, high-quality printing products like banknotes, stamps, or vouchers, are automatically checked by optical surface inspection systems.

In a typical optical surface inspection system, several digital cameras acquire the printing products with fine resolution from different viewing angles and at multiple wavelengths of the visible and also near infrared spectrum of light.

The - 30 - cameras deliver data streams with a huge amount of image data that have to be processed by an image processing system in real time.

In this contribution, a solution is proposed, where the image processing load is distributed between FPGAs and digital signal processors DSPs in such a way that the strengths of both technologies can be exploited.

The focus lies upon the implementation of image processing algorithms in an FPGA and its advantages. For the implementation of image processing algorithms in the FPGA, pipeline parallelism with clock frequencies up to MHz together with spatial parallelism based on multiple instantiations of modules for parallel processing of multiple data streams are exploited for the processing of image data of two cameras and three color channels.

Due to their flexibility and their fast response times, it is shown that FPGAs are ideally suited for realizing a configurable all-digital PLL for the processing of camera line-trigger signals with frequencies about kHz, using pure synchronous digital circuit design.

The method, presented here, consists in adding a new energy term based on the object center of gravity distance map.

This additional term acts as attraction forces that constrain the contour to remain in the vicinity of the object.

The distance map introduced here differs from the classical one since it is not based on a binary image, but rather constitutes a simplified and very fast version that relates only to one point, defined as the expected center of gravity of the object.

The additional forces, so introduced, act as a kind of balloon method with improved convergence. The method is evaluated for object segmentation in images, and also for object tracking.

The center of gravity is computed from the initial contour for each image of the sequence considered.

Compared to the balloon method, the presented approach appears to be faster and less prone to loops, as it behaves better for object tracking.

Bocharov, Mr. Sidorchuk Dmitry, I. Konovalenko, I. Koptelov Moscow Institute of Physics and Technology State University , Visillect Service Limited, Russia The study concerned deals with a new approach to the problem of detecting vehicle passes in vision-based automatic vehicle classification system.

Essential non-affinity image variations and signals from induction loop are the events that can be considered as detectors of an object presence.

We propose several vehicle detection techniques based on image processing and induction loop signal analysis.

Also we suggest a combined method based on multi-sensor analysis to improve vehicle detection performance.

Experimental results in complex outdoor environments show that the proposed multi-sensor algorithm is effective for vehicles detection.

Velislava Stoykova Institute for Bulgarian Language, Bulgarian Academy of Sciences, Bulgaria The paper describes approach to use statistically-based tools incorporated into Sketch Engine system for electronic text corpora processing to mining big textual data to search and extract word semantic properties.

It presents and compares series of word search experiments using different statistical approaches and evaluates results of Bulgarian language EUROPARL 7 Corpus search with respect to extracted word semantic properties.

Renjie Wu, Qishi Zhang and Sei-ichiro Kamata The recent years has seen immense improvement in the development of signal processing based on Curvelet transform.

The Curvelet transform provide a new multi-resolution representation. The frame elements of Curvelets exhibit higher direction sensitivity and anisotropic than the Wavelets, multi-Wavelets, steerable pyramids, and so on.

These features are based on the anisotropic notion of scaling. In practical instances, time series signals processing problem is often encountered.

To solve this problem, the time-frequency analysis based methods are studied. However, the time-frequency analysis cannot always be trusted.

Many of the new methods were proposed. The EMD aims to decompose into their building blocks functions that are the superposition of a reasonably small number of components, well separated in the time-frequency plane.

And each component can be viewed as locally approximately harmonic. However, it cannot solve the problem of directionality of high-dimensional.

We introduce a definition for a class of functions that can be viewed as a superposition of a reasonably small number of approximately harmonic components by optimized Curvelet family.

We analyze this algorithm and demonstrate its results on data. The experimental results prove the effectiveness of our method.

Aristidis Likas Department of Computer Science and Engineering, University of Ioannina, Greece An efficient shot summarization method is presented based on agglomerative clustering of the shot frames.

Unlike other agglomerative methods, our approach relies on a cluster merging criterion that computes the content homogeneity of a merged cluster.

Best Manipulation Paper Award sponsored by Ben Wegbreit The award wants to highlight innovative efforts in the planning and execution of manipulation tasks which take place in dynamic environments.

The integration of humans is also critical. Numerous challenges need to be overcome and new applications are also highly sought after.

Best Medical Robotics Paper Award sponsored by Intuitive Surgical This award will recognize outstanding work in the area of medical robotics and computer-assisted interventional devices and systems.

Relevant topics may include the design and development of novel devices and robotic systems, and their integration with navigation and imaging technologies for enhanced clinical efficacy.

Factors to be considered are: the significance of the new applications, technical merits, originality, potential impact on the field, and clarity of presentation.

Factors to be considered are: Technical merit, originality, potential impact on the field, practical significance for applications, and clarity of the video presentation.

Factors to be considered are: Technical merit, originality, potential impact on the field, practical significance of the applications, clarity of the written presentation in the proceedings, and quality of the oral presentation at the conference.

Factors to be considered are: Technical merit, originality, potential impact on the field, clarity of the written paper, and quality of the oral or other presentation.

Similar efforts have been undertaken in the United States, Europe, and Asia with mixed results. You will hear from researchers, vendors, and funding agencies on their experiences and the roadblocks they have encountered.

A panel discussion will conclude the forum to foster dialog between participants and speakers. Based on the discussions stemming from the entire day, a white paper will be published with an action plan to go from where we are to where we can.

The target audience of the forum is end-users, developers, vendors, and anyone who is interested in robotics and automation technologies.

What can government agencies do to foster such collaboration and facilitate innovation and technology transfer? How can the end-users and the community at-large benefit from the above three groups working as a cohesive whole?

What are known and hidden and not-so-widely discussed barriers and roadblocks? What is the role of standardization and ad-hoc standards and best practices?

Can the support of entrepreneurship address some of the aforementioned problems? How can we leverage existing know-how and target the low-hanging fruit as well as long-term issues in a collaborative fashion?

Agenda The final list of speakers is yet to be confirmed. The Innovation Corps is an aggressive new program to train students and principal investigators in the subtleties of commercializing output of basic research.

Researchers with NSF-sponsored research ideas that they believe are nearing commercial potential can apply for funding to help determine the business potential of ground-breaking ideas.

However, some believe entrepreneurial education has failed to deliver substantive changes in the success rate of technology-based start-up businesses in the United States.

NSF has adopted an emerging new curriculum being championed at select universities that formulates business creation as a methodology familiar to engineers and scientists: hypothesis testing.

By capturing this methodology and introducing it to educators, engineers and scientists, the Innovation Corps endeavors to construct an innovation ecosystem that more efficiently captures the fruits of government investment in long-term research for job creation and economic development.

This bold new program has been garnering deep interest from government agencies and entrepreneurial educators around the world. In an economic climate that presents increasing challenges due to the accelerating pace of technological change, dwindling natural resources, rising unemployment, and spiraling populations, greater efficiency in translating academic advances into meaningful impact on society is relevant to all.

The ICRA "Birds of a Feather" Women Luncheons offer the opportunity to young female researchers to discuss informally with senior faculty members around a free lunch.

Free lunch will be available on a first-come, first-served basis to ICRA women attendees. This luncheon was initiated within the RAS Technical Activities Board TAB as a means to let graduates be aware of what the society has to offer, and to network with each other.

The opportunity is also used to present the structure of the society, and introduce the various Technical Committees forming TAB.

RAS members will have first priority. If you are not yet a member, you can sign up now at www. Pre-registration required. Lunch with Leaders LwL was initiated by the Student Activities Committee with the aim to provide students with an opportunity to get in contact with leaders and get advice and mentoring on their career and research.

Leaders in attendance will include: Antal Bejczy, T. RAS members will be prioritized. From May 14 to May 18, the conference will showcase technical sessions, workshops, tutorials, and exhibits reflecting advances in our rapidly developing field.

The convention center is located in downtown Saint Paul overlooking the Mississippi River. The walk from RiverCentre to Crowne Plaza, the main conference hotel, takes about eight minutes along Kellogg Boulevard.

All workshops, technical sessions, exhibits and robotics challenges will be held at the RiverCentre. Minneapolis and Saint Paul constitute a vibrant metro area known as the Twin Cities.

The area is also a major hub for arts, sports, education and entertainment. Together with its numerous parks, lakes, biking and hiking trails, the Twin Cities have something fun and exciting for any taste.

Located on Kellogg Boulevard and overlooking the Mississippi River, the Science Museum of Minnesota offers guests a unique opportunity to explore all kinds of science learning.

With nearly nine acres of indoor space devoted to hands-on science activities, a state-of-the-art giant screen theater, and an outdoor exhibit gallery featuring science-themed mini-golf and a 17, square-foot prairie maze, the Science Museum of Minnesota has something for visitors of all ages and backgrounds to enjoy.

In the Science Museum of Minnesota's Experiment Gallery, visitors can carry out simple experiments and find the joy of discovery as they uncover the fundamental properties of physical events.

They can explore energy transformation, weather, air dynamics, light, waves and resonance, and more.

The Science Museum of Minnesota's Cell Lab offers visitors an opportunity to don a lab coat and gloves to explore the world of cells through creative experiments.

One of the highlights of the museum's Dinosaurs and Fossils Gallery is an foot-long Diplodocus , a plant-eating dinosaur from the Jurassic period.

With St. A perennial summer visitor favorite, the Big Back Yard features a science-style mini-golf course, a 17,square foot prairie maze, gardens, and an award-winning solar-powered building.

During the conference, SMM will also feature a Pirates exhibit! Try out one of these sample itineraries, as recommended by our volunteers!

During the conference, a new exhibit featuring a rare, early published version of the U. Constitution and an even more rare draft of the Bill of Rights, along with the original editions of the two state of Minnesota Constitutions, will be on display.

How to get there: The walk from the RiverCentre takes about ten minutes. Listed on the national register of historic places and featured in several movies, the Food Network and travel TV programs, Mickey's is an authentic 's Art Deco diner.

The diner has been serving up breakfast, lunch and dinner 24 hours a day for nearly 70 years. For more see www. Paul: Take a fifteen minute walk from the RiverCentre to see one of the most prominent attractions of St.

Jonathan Padelford: Enjoy the splendor of the Mississippi with a ride on the Jonathan Padelford, an authentic sternwheeler riverboat.

A historically narrated public sightseeing excursion departs at 2P. The tour runs for 90 minutes. Sights on the way include: the St.

Tours depart from Harriet Island, which is directly across the river from the Science Museum. Wabasha Street Caves: These manmade caves have historically been used for growing mushrooms and for the storage of food.

The caves are said to be haunted this one is definitely true. The walk is about fifteen minutes from the Crowne Plaza, and twenty from the RiverCentre.

Paul was transitioning from a town to a city, and the business leaders of the day used their newfound wealth to build themselves mansions on the hill overlooking their empire.

Many of these mansions are still standing today, under the shade of broad trees, stretching from the Cathedral of St. Highlights include the James J.

Scott Fitzgerald lived. If you get tired of houses and trees you can stop for a bite to eat on Selby Avenue near the Cathedral, or alternatively near the intersection of Grand Avenue and Victoria a block south of Summit Ave.

Both areas were once streetcar stops which allowed commercial districts to build up in mostly residential areas. Though the street car is long gone, the commercial areas remain, and they are popular local destinations.

Visit www. How to get there: The conference is planning to provide shuttles to MoA. Please check the information booth by the registration area in RiverCentre for departure information.

You can also take Bus 54 Express Route on 5 th Avenue. The trip there is about half an hour. Summit Brewery: If you are taking public transportation, you can stop by the Summit Brewery along the way.

Summit is a uniquely Minnesotan beer, and a local favorite. The Brewery offers free tours and free samples, and has a gift shop on site.

Disembark on Otto Avenue. Conference Locations Minneapolis Our suggested itinerary for Minneapolis starts from the Minneapolis Central Library make sure to peek inside!

The walk takes about thirty minutes. The best place to enter the skyway system is through the Gaviidae Commons home to Nieman Marcus, the premium outlet Saks Off 5th, and other upscale shopping and dining areas.

The Center is home to a nice indoor plaza and to more affordable lunch options. Between the IDS center and Target flagship store, you can stop by Barnes and Noble bookstore , go to Panera for quick sandwich, or enjoy Zelo; an upscale restaurant featuring American and Italian fusion cuisine.

The Local is a great spot to catch the latest European soccer match on TV. In the middle of the next block, Loring Greenway leads away from the street to the west.

Featuring over 40 permanent art installations, the Minneapolis Sculpture Garden is one of the largest urban sculpture gardens in America.

The Walker Art Center is one of the nation's five biggest museums showcasing modern art. For more information see www. Route 16 and 50 , but 94 is the fastest.

There are about one hundred theaters in the Twin Cities. The Washington Avenue Bridge connects the two banks with dedicated pedestrian and bike lanes.

The bridge provides excellent views of the Mississippi and of downtown Minneapolis. The Union is a hub of recreational student activities.

Notable architecture on campus includes the Weisman building picture below and the Armory building. You can also take buses Route 3, 16, and 50 from the Crowne Plaza Hotel to the campus about 55 minutes.

The University operates a regular, free shuttle service around the campus. Riverfront District: Close to the University of Minnesota is the historic Riverfront district featuring a museum, observation decks, restaurants with live outdoor music, jogging and biking trails.

The Saint Anthony Riverfront complex situated next to the Hennepin Island Park offers numerous sports restaurants and bars with live outdoor music in the summer.

Biking trails run across both banks of Mississippi, and rental bikes are available at nearby locations from Nice Ride MN.

How to get there: From St. If you are coming from the university campus, you can walk directly about 15 minutes , or take bus route 6 at the 4th Street and 15th Avenue SE bus stop and get off at the 4th Street and 4th Avenue SE bus stop this takes about six minutes.

The tours will give participants the opportunity to visit research exhibits and attend robotics and computer vision demonstrations from the research groups of faculty at the UMN including, among others: Maria Gini, Volkan Isler, Bernice Mettler, Nikos Papanikolopoulos, and Stergios Roumeliotis.

The tours are free and include transportation. Pre-registration is required. Please view the conference website for more information after May 1st.

Children Minnesota offers some wonderful activity options for families with kids. Both the Science Museum across from the conference venue and the Children's Museum a couple of blocks North provide all day fun and learning.

The Mall of America is a must-see. You might also consider visiting Como Park. Como Park also houses a small zoo, which is free and open every day of the week.

The weather is highly variable. Temperatures in the mids or the 30s are not unheard of for this time of the year.

Most days are sunny but intense rainstorms can arrive with little warning. Humidity ranges from medium to high. Dressing in layers is advisable.

Shuttles The conference is planning to provide shuttles to downtown Minneapolis in the evening and the Mall of America during the day.

The shuttles will pick up and drop off from the RiverCentre on Kellogg Boulevard. Paul International Airport is available for a fee please see below for discount information.

ExecuCar must be reserved and pre-paid in advance. Terminal 2 Southwest, Sun Country, Air Tran : Proceed across the street from the terminal; the ground transportation center is located on the ground floor of the parking ramp.

Pick up the courtesy phone at the blue and yellow SuperShuttle Kiosk and you will be automatically connected to a local agent.

Please note, these are non-commissionable discount rates. This is just a small sampling of what Saint Paul has to offer. The places listed below are perfect for those on a student budget: American Cajun Grill 56 6th Street East, Suite Locally renowned breakfast served until close at 3PM.

Patio seating. Dine-ins are also welcome. Simple, good food. Burger Moe's West 7th Street - Patio seating.

Sixty beers from around the world forty of them on tap. Just two blocks from the Xcel Energy Center. Cafeteria-style Italian deli and pizzeria.

Rooftop seating offered. Emphasis on healthy, natural ingredients. Erberts is a Wisconsin-based chain. Around since Lots of character.

Gastrotruck A food truck, serving pub-style treats including sliders, crudo, and tacos. Call to find out where they are parked!

A French bistro in the sky way! Meritage Crepe Stand St. The Stand is open Tuesdays Fridays, 11A. Both sweet and savory crepes are available.

Paul around-the-clock since A classic diner experience. NY-style pizza. Food court location. Both sweet and savory pies offered.

Skyway location. Quick service. The salads are recommended. Barrio 6th Street East Full bar. Most award-winning sushi restaurant in the Twin Cities.

Latin American street food. Small plates. Great bar. Lively atmosphere. Handcrafted beer. Patio dining.

Very close to Xcel Energy Center. Char house and lounge. Signature dishes include fire-roasted meats, fish cooked in the Persian tradition.

American fare. Free wireless. Sixteen TV screens. Urban bistro. Dinner Only. Newly remodeled. Full-length sushi bar.

Paul Grill Market Street Exceptional bar. New American. Happy Hour everyday, P. Classic American dining. Sustainable, locally raised and grown ingredients used.

Bosch 5-delni set SDS-plus dleta i hamer burgija Gerd Baltus - agentur regine schmitz www. The provided results also facilitate the precision selection for more info performance or for some performance-complexity tradeoff. To reduce the complexity of the stereovision or one-cameral calculating the target of three-dimensional coordinates, Wutprobe the ultra-wideband radar distance module provides visual depth information, real-time Image-PTU tracking UAV and calculate Kino Bremen UAV three-dimensional coordinates. The general issues mentioned above will be presented. We present the partially parallel extension of the mixed-domain decoder that operates for the structured codes. At the same time, several natural privacy and legal concerns appear for people wearing devices at all Die Bestimmung Alle that can record video and take pictures. In order to identify all weather UAV targets, we use infrared cameras. Advise Maria Furtwängler final technical sessions are accompanied by special tutorials where we invited here world experts to share their knowledge. Great bar.

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