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Efficient CRC concatenation scheme for polar codes

ELECTRONICS LETTERS 2017年第13期53卷 860-861页

作者： Zhang Qingshuang Liu Aijun Pan Xiaofei PLA Univ Sci & Technol Coll Commun Engn 1 Haifuxiang Rd Nanjing 210007 Jiangsu Peoples R China

A new cyclic redundancy check (CRC) concatenation with polar codes based on partial protection is proposed, where only the crucial bits chosen from the total information bits are protected with the CRC. The index set of crucial bits is determined by the row weight of generator matrix of polar codes and the indexes with minimum row weight make up this crucial set. Using this new concatenation, the number of polar codewords with minimum Hamming weight can be efficiently decreased. Simulation results show that the performance of the proposed partial protection scheme owns a lower error floor than that of the classical blind protection.

关键词： computer vision image sensors Kinect v1 depth images computer vision algorithms empirical noise model synthetic Kinect depth images

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Expert, Crowd, Students or Algorithm: who holds the key to deep-sea imagery 'big data' processing?

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METHODS IN ECOLOGY AND EVOLUTION 2017年第8期8卷 996-1004页

作者： Matabos, Marjolaine Hoeberechts, Maia Doya, Carol Aguzzi, Jacopo Nephin, Jessica Reimchen, Thomas E. Leaver, Steve Marx, Roswitha M. Albu, Alexandra Branzan Fier, Ryan Fernandez-Arcaya, Ulla Juniper, S. Kim IFREMER Ctr Bretagne REM EEP Lab Environm Profond F-29280 Plouzane France Univ Victoria Ocean Networks Canada Victoria BC V8W 2Y2 Canada Univ Victoria Dept Comp Sci Victoria BC Canada CSIC Inst Marine Sci ICM Paseo Maritimo Barceloneta 37-49 E-08003 Barcelona Spain Univ Victoria Dept Biol Victoria BC Canada Univ Victoria Dept Elect & Comp Engn Victoria BC Canada Univ Victoria Sch Earth & Ocean Sci Victoria BC Canada

1. Recent technological development has increased our capacity to study the deep sea and the marine benthic realm, particularly with the development of multidisciplinary seafloor observatories. Since 2006, Ocean Networks Canada cabled observatories, have acquired nearly 65 TB and over 90 000 h of video data from seafloor cameras and remotely operated vehicles. Manual processing of these data is time-consuming and highly labour-intensive, and cannot be comprehensively undertaken by individual researchers. These videos are a crucial source of information for assessing natural variability and ecosystem responses to increasing human activity in the deep sea. 2. We compared the performance of three groups of humans and one computer vision algorithm in counting individuals of the commercially important sablefish (or black cod) Anoplopoma fimbria, in recorded video from a cabled camera platform at 900 m depth in a submarine canyon in the Northeast Pacific. The first group of human observers were untrained volunteers recruited via a crowdsourcing platform and the second were experienced university students, who performed the task for their ichthyology class. Results were validated against counts obtained from a scientific expert. 3. All groups produced relatively accurate results in comparison to the expert and all succeeded in detecting patterns and periodicities in fish abundance data. Trained volunteers displayed the highest accuracy and the algorithm the lowest. 4. As seafloor observatories increase in number around the world, this study demonstrates the value of a hybrid combination of crowdsourcing and computer vision techniques as a tool to help process large volumes of imagery to support basic research and environmental monitoring. Reciprocally, by engaging large numbers of online participants in deep-sea research, this approach can contribute significantly to ocean literacy and informed citizen input to policy development.

关键词： computer vision algorithms crowdsourcing deep-sea imagery Digital Fishers fish counting OceanNetworks Canada seafloor observatories underwater video

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Breast MRI Radiogenomics: Current Status and Research Implications

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JOURNAL OF MAGNETIC RESONANCE IMAGING 2016年第6期43卷 1269-1278页

作者： Grimm, Lars J. Duke Univ Med Ctr Dept Radiol Box 3808 Durham NC 27710 USA

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed.

关键词： MRI breast cancer radiogenomics computer vision algorithms genetics

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vision-based Offline-Online Perception Paradigm for Autonomous Driving 15

Vision-based Offline-Online Perception Paradigm for Autonomo...

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IEEE Winter Conference on Applications of computer vision (WACV 2015)

作者： Ros, German Ramos, Sebastian Granados, Manuel Bakhtiary, Amir Vazquez, David Lopez, Antonio M. Comp Vis Ctr Campus UAB Barcelona Spain Univ Autonoma Barcelona Barcelona Spain Univ Oberta Catalunya Barcelona Spain

ISBN: (纸本)9781479966837

Autonomous driving is a key factor for future mobility. Properly perceiving the environment of the vehicles is essential for a safe driving, which requires computing accurate geometric and semantic information in real-time. In this paper, we challenge state-of-the-art computer vision algorithms for building a perception system for autonomous driving. An inherent drawback in the computation of visual semantics is the trade-off between accuracy and computational cost. We propose to circumvent this problem by following an offline-online strategy. During the offline stage dense 3D semantic maps are created. In the online stage the current driving area is recognized in the maps via a re-localization process, which allows to retrieve the pre-computed accurate semantics and 3D geometry in real-time. Then, detecting the dynamic obstacles we obtain a rich understanding of the current scene. We evaluate quantitatively our proposal in the KITTI dataset and discuss the related open challenges for the computer vision community.

关键词： computer vision geometry real-time systems road safety traffic information systems 3D geometry KITTI dataset autonomous driving computer vision algorithms future mobility geometric information real-time system safe driving semantic information vision-based offline-online perception paradigm Cameras computer vision Semantics Sensors Three-dimensional displays Vehicle dynamics Vehicles images computer vision real-time systems Defensive driving three-dimensional displays Semantics Traffic information systems vehicle Vehicle dynamics Road safety Cameras Sensors semiotics geometry

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The analysis of selected orientation methods of architectural objects' scans 13

The analysis of selected orientation methods of architectura...

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Conference on Videometrics, Range Imaging, and Applications XIII

作者： Markiewicz, Jakub S. Kajdewicz, Irmina Zawieska, Dorota Warsaw Univ Technol Dept Photogrammetry Remote Sensing & Spatial Info Fac Geodesy & Cartog PL-00661 Warsaw Poland

ISBN: (纸本)9781628416886

The terrestrial laser scanning is commonly used in different areas, inter alia in modelling architectural objects. One of the most important part of TLS data processing is scans registration. It significantly affects the accuracy of generation of high resolution photogrammetric documentation. This process is time consuming, especially in case of a large number of scans. It is mostly based on an automatic detection and a semi-automatic measurement of control points placed on the object. In case of the complicated historical buildings, sometimes it is forbidden to place survey targets on an object or it may be difficult to distribute survey targets in the optimal way. Such problems encourage the search for the new methods of scan registration which enable to eliminate the step of placing survey targets on the object. In this paper the results of target-based registration method are presented The survey targets placed on the walls of historical chambers of the Museum of King Jan III's Palace at Wilanow and on the walls of ruins of the Bishops Castle in Ilza were used for scan orientation. Several variants of orientation were performed, taking into account different placement and different number of survey marks. Afterwards, during next research works, raster images were generated from scans and the SIFT and SURF algorithms for image processing were used to automatically search for corresponding natural points. The case of utilisation of automatically identified points for TLS data orientation was analysed. The results of both methods for TLS data registration were summarized and presented in numerical and graphical forms.

关键词： automatic TLS registration target-based methods spherical images computer vision algorithms accuracy orthoimages

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computer based quantification of normal and pathological vocal folds phonatory processes from laryngovideostroboscopy

Computer based quantification of normal and pathological voc...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Kopczynski, Bartosz Strumillo, Pawel Niebudek-Bogusz, Ewa Lodz Univ Technol Inst Elect Ul Wolczanska 211-215 PL-90924 Lodz Poland Nofer Inst Occupat Med Dept Audiol & Phoniatr PL-91348 Lodz Poland

ISBN: (纸本)9788360810668

Medical imaging techniques offer novel visualization and analysis methods of the vocal folds during phonation and automatic computation of indices aiding the phoniatrist in a more precise diagnosis of voice disorders. The aim of this study is to apply computer vision algorithms for qualitative and quantitative analysis of vocal folds' vibrations. Videostroboscopic examinations of the larynx were carried out for 30 patients. Image pre-processing and image segmentation algorithms were applied to compute the glottis area during phonation. The glottovibrograms which are spatio-temporal visualizations of the vibrating vocal folds were also built. The proposed indices allow for a quantitative and comparative analysis of normal and disordered phonatory processes. The conducted pilot study has confirmed the validity of the computer aided imaging methods for the qualitative and quantitative analysis of the videostroboscopic images of the phonatory motions of the vocal folds.

关键词： computer vision image segmentation medical image processing video signal processing analysis methods automatic index computation comparative analysis computer aided imaging methods computer based quantification computer vision algorithms disordered phonatory process glottis area glottovibrograms image preprocessing laryngovideostroboscopy larynx medical imaging techniques normal phonatory process normal vocal fold phonatory process pathological vocal fold phonatory process phonation phonatory motions qualitative analysis quantitative analysis spatio-temporal visualizations videostroboscopic images visualization methods vocal fold vibrations voice disorder diagnosis Algorithm design and analysis Cameras computers Image segmentation Larynx Pathology Videos image segmentation Vocal Cords Larynx images computers Phonation computer vision Algorithm design and analysis visualization methods QUANTITATIVE ANALYSIS Video signal processing Medical image processing Videotapes Cameras pathology

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Partially occluded pedestrian classification using histogram of oriented gradients and local weighted linear kernel support vector machine

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IET computer vision 2014年第6期8卷 620-628页

作者： Aly, Saleh Aswan Univ Dept Elect Enginnering Comp & Syst Sect Fac Engn Aswan 81542 Egypt

One of the main challenges in pedestrian classification is partial occlusion. This study presents a new method for pedestrian classification with partial occlusion handling. The proposed method involves a set of part-based classifiers trained on histogram of oriented gradients features derived from non-occluded pedestrian data set. The score of each part classifier is then employed to weight features used to train a second stage full-body classifier. The full-body classifier based on local weighted linear kernel support vector machine is trained using both non-occluded and artificially generated partial occlusion pedestrian dataset. The new kernel allows to significantly focus on the non-occluded parts and reduce the impact of the occluded ones. Experimental results on real-world dataset, with both partially occluded and non-occluded data, show high performance of the proposed method compared with other state-of-the-art methods.

关键词： pedestrians computer vision algorithms image classification nonoccluded pedestrian data set local weighted linear kernel support vector machine traffic engineering computing Image recognition histogram of oriented gradient features full-body classifier artificially generated pedestrian dataset support vector machines part-based classifiers Traffic engineering computing computer vision computer vision and image processing techniques partially occluded pedestrian classification Knowledge engineering techniques second stage full-body classifier

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FPGA-based Path-planning of High Mobility Rover for Future Planetary Missions

FPGA-based Path-planning of High Mobility Rover for Future P...

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19th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2012)

作者： Lentaris, G. Diamantopoulos, D. Stamoulias, G. Siozios, K. Soudris, D. Aviles Rodrigalvarez, M. Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece GMV Adv Space Syst & Technol Madrit Spain

ISBN: (纸本)9781467312608

Work in navigational autonomy for planetary exploration rovers has focused on achieving safe and efficient path-planning through unknown, rocky terrain. computer vision is playing an important role in increasing autonomy of both spacecraft and robotic vehicles, however due to their increased computational complexity, they are rarely implemented onto conventional computing systems. This problem becomes far more severe whenever real-time constraints have also to be considered. This paper addresses progress on rover path planning for high mobility mars rover missions. More specifically, at SPARTAN project, a demonstrator is being developed that meets ESA's specifications for the problem of rover Localization. This problem accounts for the generation of location estimates. This process involves four distinct applications: Imaging, 3D-Reconstruction, Visual Odometry (VO) and Visual Simultaneous Localization and Map reconstruction (SLAM). On supporting these functions we developed a novel HW/SW co-design methodology that extracts parallelism in higher algorithmic level, and thus allows the simultaneous execution of computational intensive kernels on a FPGA device, while the control flow is maintained by a low-performance CPU. Experimental results show that our implementation achieves the scopes of SPARTAN project.

关键词： computer vision algorithms Space Application FPGA implementation High-Performance HW/SW co-design

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Gesture Therapy: A vision-Based System for Upper Extremity Stroke Rehabilitation

Gesture Therapy: A Vision-Based System for Upper Extremity S...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Enrique Sucar, L. Luis, Roger Leder, Ron Hernandez, Jorge Sanchez, Israel Inst Nacl Astrofis Opt & Electr Luis Enrique Erro 1 Puebla Mexico Univ Nacl Autonoma Mexico Mexico City DF Mexico Inst Nacl Neurol & Neurocirujia Mexico City DF Mexico

ISBN: (纸本)9781424441242

Stroke is the main cause of motor and cognitive disabilities requiring therapy in the world. Therefor it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. We have developed a low-cost vision-based system that allows stroke survivors to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a virtual environment for facilitating repetitive movement training, with computer vision algorithms that track the hand of a patient, using an inexpensive camera and a personal computer. This system, called Gesture Therapy, includes a gripper with a pressure sensor to include hand and finger rehabilitation;and it tracks the head of the patient to detect and avoid trunk compensation. It has been evaluated in a controlled clinical trial at the National Institute for Neurology and Neurosurgery in Mexico City, comparing it with conventional occupational therapy. In this paper we describe the latest version of the Gesture Therapy System and summarize the results of the clinical trail.

关键词： arm movement biomechanics biomedical optical imaging computer vision computer vision algorithms finger rehabilitation gesture therapy gripper grippers hand rehabilitation inexpensive camera intensive movement training medical computing medical image processing occupational therapy patient rehabilitation personal computer pressure sensor pressure sensors trunk compensation upper extremity stroke rehabilitation virtual environment vision-based system

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Tracking all traffic - computer vision algorithms for monitoring vehicles, individuals, and crowds

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IEEE ROBOTICS & AUTOMATION MAGAZINE 2005年第1期12卷 29-36页

作者： Maurin, B Masoud, O Papanikolopoulos, NP Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA LSIIT Strasbourg France

This article presents a vision-based system for monitoring crowded urban scenes. The approach combines an effective detection scheme based on optical flow and background removal that can locate vehicles, individual pedestrians, and crowds. The detection phase is followed by the tracking phase that tracks all the detected entities. Traffic objects are not simply tracked but a wealth of information (position, velocity, acceleration/deceleration, bounding rectangle, and shape features) is gathered about them also. Potential applications of the methods include intersection control, traffic data collection, and even crowd control after athletic events. Extensive experimental results for a variety of weather conditions are presented. Future work would focus on methods to deal with shadows and occlusions.

关键词： monitoring systems computer vision algorithms intersections vision-based system tracking schemes traffic objects crowds

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