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International Conference on computer vision Workshops (ICCV Workshops)

作者： Chunmei Liu Changbo Hu J.K. Aggarwal Department of Computer Science and Technology Tongji University Shanghai China Computer & Vision Research Center University of Texas at Austin USA

An eigenshape kernel based mean shift tracker is proposed in this paper. In contrast with the symmetric constant kernel used in the traditional mean shift tracker, this tracker employs eigenshape to construct an arbitrarily shaped kernel that is adaptive to object shape. Therefore, background information is adaptively excluded from the target. Furthermore, the eigenshape kernels are integrated with color and gradient features, which enhance tracking robustness. Experiments demonstrate that this tracker outperforms the traditional mean shift tracker significantly especially when target shape deformation, target occlusion and background clutter occur.

关键词： Kernel Shape Target tracking Histograms Image color analysis Humans

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Retinal vessel tortuosity evaluation via Circular Hough Transform

Retinal vessel tortuosity evaluation via Circular Hough Tran...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Farnoosh Ghadiri HamidReza Pourreza Touka Banaee Morteza Delgir Computer Engineering Department Machine Vision Laboratory Ferdowsi University of Mashhad Iran Computer Engineering Department Machine Vision Laboratory University of Ferdowsi Mashhad Iran Ophthalmic Research Center Khatam-Al-Anbia Hospital Medical science University of Mashhad Iran Computer Science Department Robotics Laboratory Northeastern University USA

Retinal vessel tortuosity has shown to be significantly associated with cardiovascular diseases such as hypertension and diabetes. Despite importance of this field a few techniques have been proposed yet. All previous methods rely on a vessel extraction phase, which its accuracy affects final output and also time consuming. Nobility of presented algorithm is to introduce a method for evaluating retinal vessel tortuosity without any explicit vessel detection. We use the Circular Hough Transform (CHT) based on gradient field of the retinal image. Each vessel curve is detected as a semi-circle by Hough transform and tortuosity of the curve is determined with the help of accumulated value of circle center and its radius. As there are no any specific database for tortuosity evaluation, the algorithm was tasted on database consisting of 40 images, mixture of DRIVE database and images from Khatam-Al-Anbia Hospital consisting of 40 retinal images, of which 20 were tortuous and 20 were non-tortuous. The proposed algorithm can achieve classification rate of 92% along with less computation time in compare of previous methods.

关键词： Transforms Retinal vessels Classification algorithms Biomedical measurements Biomedical imaging Image segmentation

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An accurate 3D feature tracking system with wide-baseline stereo smart cameras

An accurate 3D feature tracking system with wide-baseline st...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Dominik Rueß Kristian Manthey Ralf Reulke German AeroSpace Center Optical Information Systems Institute of Robotics and Mechatronics Berlin Germany Department of Computer Science Research and Lecture Group Computer Vision Humboldt-Universität zu Berlin Berlin Germany

A typical video surveillance system consists of at least one camera, controlled by an operator. To decrease the human error rate and to generally lessen the burden of operators, many object tracking systems have been implemented, most of which work in 2D image space. If used centralized, this is a very expensive task. Furthermore, if several views are to be fused, large inaccuracies arise due to ground plane assumptions, for instance. Lastly, in outdoor setups, quite often there is a need for slower channels like Wireless LAN which cannot cope with the full resolution data stream. We provide a smart camera system which performs the intensive tasks like background estimation or feature extraction. A central unit only has to process the received data in feature space, increasing scalability. Additionally, the object tracking problem is converted to an accurate 3D feature tracking, avoiding difficulties such as proper object segmentation and adding increased trajectory accuracy. The feature regions are computed within the smart camera. A wide-baseline feature matching approach has been employed to allow more freedom in the placement of the single smart cameras.

关键词： Trajectory Three dimensional displays Cameras Smart cameras Estimation Image reconstruction Feature extraction

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Beta-eigenspaces for autonomous mobile robotic trajectory outlier detection

Beta-eigenspaces for autonomous mobile robotic trajectory ou...

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2011 IEEE International Conference on Technologies for Practical Robot Applications, TePRA 2011

作者： Zaheer, Shyba Gulrez, Tauseef Deaprtment of Electrical Engineering College of Engineering and Applied Sciences Al Ghurair University Dubai Academic City United Arab Emirates Department of Computer Science Center for Intelligent Machines and Robotics Research COMSATS Institute of Information Technology Lahore Pakistan

ISBN: (纸本)9781612844824

This paper addresses the problem of robotics trajectory building for efficient navigation and consequently exploration. A concept of beta-eigenvector has been introduced to find an outlier for the existing non-point based trajectory obtained from raw laser data. We have used our paradigm of "free configuration eigenspaces" method [1], with specific focus on outlier detection. The key idea proposed in this paper is to replace the Gaussian distribution utilized by the probabilistic principal component analysis (PPCA) with the beta-distribution. It is a well known issue that the conventional PCA is sensitive to anomalous observations because the calculation of sample mean and covari-ance matrix can be significantly influenced by a small number of outliers. Similarly, PPCA is not robust to outliers since the data are assumed to follow a multivariate Gaussian distribution that is easily affected by deviant observations. An outlier detection is done using Beta-Probabilistic Principal Component Analysis (BPPCA), further more an analysis is proposed to identify which variables contribute the most to the occurrence of outliers. The proposed technique is applied on real-time robotics sensor data as well as on the real-time robotics simulation environment. © 2011 IEEE.

关键词： Gaussian distribution

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Multiagent communication security in adversarial settings

Multiagent communication security in adversarial settings

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2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011

作者： Okamoto, Steven Paruchuri, Praveen Wang, Yonghong Sycara, Katia Marecki, Janusz Srivatsa, Mudhakar Computer Science Department Carnegie Mellon University Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States IBM T.J. Watson Research Center Hawthorne NY United States

ISBN: (纸本)9780769545134

In many exciting multiagent applications - including future battlefields, law enforcement, and commerce - agents must communicate in inherently or potentially hostile environments in which an adversaries disrupt or intercept the communication between agents for malicious purposes, but the wireless ad hoc networks often proposed for these applications are particularly susceptible to attack. Intelligent agents must balance network performance with possible harm suffered from an adversary's attack, while accounting for the broadcast nature of their communication and heterogenous vulnerabilities of communication links. Furthermore, they must do so when the adversary is also actively and rationally attempting to counter their efforts. We address this challenge in this paper by representing the problem as a game between a sender agent choosing communication paths through a network and an adversary choosing nodes and links to attack. We introduce a network-flow-based approach for compactly representing the competing objectives of network performance and security from adversary attack, and provide a polynomial-time algorithm for finding the equilibrium strategy for the sender. Through empirical evaluation we show how this technique improves upon existing approaches. © 2011 IEEE.

关键词： Network security

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational Systems, Commonsense Knowledge, Complex Adaptive Systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational Systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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A Cascade Traffic Accident Recognition System Using Multi-sensor Cooperation

A Cascade Traffic Accident Recognition System Using Multi-se...

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International Conference on computer Communication and Management（ICCCM 2011）

作者： Ilkyun Jung Seung-Hun Kim Minho Lee Sung-Bae Cho Intelligent Robotics Research Center Korea Electronics Technology Institute School of Electronics Engineering Kyungpook University Department of Computer Science Yonsei University

This paper presents a cascade system to reliably recognize traffic accidents using multi-sensor cooperation. The system is consisted of a MSN (Master Sensor Node) and number of SN (Sensor Node)s with both low cost DSP and CCD. Each SN computes probabilities of accident with a set of images over time taken at different locations. Once more than one accident being reported, MSN is stimulated and conducts a synthetic decision making process with various information taken from each SN related to the accident. Experimental results show that the proposed cascade system drastically enhance reliability of traffic accident recognition and enables to be set in real environments.

关键词： traffic accident recognition, cascade system, multi-senor cooperation, SN, MSN

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Wireless sensor network system for supporting nursing context-awareness

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International Journal of Autonomous and Adaptive Communications Systems 2011年第4期4卷 361-382页

作者： Naya, Futoshi Ohmura, Ren Miyamae, Masakazu Noma, Haruo Kogure, Kiyoshi Imai, Michita NTT Communication Science Laboratories 2-4 Hikaridai Seika-cho Soraku-gun Kyoto 619-0237 Japan Department of Computer Science Toyohashi University of Technology 1-1 Hibari-ga-oka Tenpaku-cho Toyohashi Aichi 441-8580 Japan WESTUNITIS Co. Ltd. 3F Funakoshi Center Bldg. 2-4-6 Funakoshi-cho Chuo-ku Osaka 540-0036 Japan Intelligent Robotics and Communication Laboratories Advanced Telecommunications Research Institute International 2-2-2 Hikaridai Seika-cho Soraku-gun Kyoto 619-0288 Japan Department of Robotics Kanazawa Institute of Technology 3-1 Yatsukaho Hakusan Ishikawa 924-0838 Japan Department of Information and Computer Science Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan

We developed a wireless sensor network system for supporting context-awareness of nursing activities in hospitals. Our system is aimed at automated recording of nursing work, providing context-aware services to nurses and visualising analytical results from nursing histories. The system consists of heterogeneous devices utilising three kinds of wireless networks: a ZigBeeTM (ZigBee is a registered trademark of the ZigBee Alliance)-based location sensor network, a BluetoothTM (Bluetooth is a trademark owned by Bluetooth SIG, Inc., USA)-based body-area sensor network for capturing nurse activities and a Wi-FiTM (Wi-Fi is a registered trademark of the Wi-Fi Alliance)-based network for communication between PDAs worn by nurses and a server PC. We illustrate the layered structure of the entire system as well as algorithms for estimating nurse locations and activities during their operations in a hospital. These estimated results are managed by a real-time database system with which nurse contexts can be visualised in real time on a server PC and/or PDAs. We also show empirical results evaluating the performance of retrieving, analysing and visualising detailed nursing contexts. Copyright © 2011 Inderscience Enterprises Ltd.

关键词： Wireless local area networks (WLAN)

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Reports of the AAAI 2010 spring symposia

Reports of the AAAI 2010 spring symposia

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作者： Barkowsky, Thomas Bertel, Sven Broz, Frank Chaudhri, Vinay K. Eagle, Nathan Genesereth, Michael Halpin, Harry Hamner, Emily Hoffmann, Gabe Hölscher, Christoph Horvitz, Eric Lauwers, Tom McGuinness, Deborah L. Michalowski, Marek Mower, Emily Shipley, Thomas F. Stubbs, Kristen Vogl, Roland Williams, Mary-Anne Cognitive Systems Group University of Bremen Research Center SFB/TR 8 Spatial Cognition Germany Human Factors Division Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign IL United States Adaptive Systems Research Group Computer Science Department University of Hertfordshire United Kingdom Artificial Intelligence Center at SRI International United States Txteagle Inc. MIT Media Laboratory United States Computer Science Department Stanford University United States University of Edinburgh United Kingdom Robotics Institute Carnegie Mellon University United States Palo Alto Research Center United States Center for Cognitive Science University of Freiburg Germany CREATE lab Carnegie Mellon Robotics Institute United States Rensselaer Polytechnic Institute United States University of Southern California United States Department of Psychology Temple University Spatial Intelligence and Learning Center United States IRobot Corporation United States Stanford Program in Law Science and Technology Stanford University Law School United States Innovation and Enterprise Research Laboratory University of Technology Sydney Australia

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's department of computer science, presented the 2010 Spring Symposium Series Monday through Wednesday, March 22-24, 2010, at Stanford University. The titles of the seven symposia were Artificial Intelligence for Development;Cognitive Shape Processing;Educational robotics and Beyond: Design and Evaluation;Embedded Reasoning: Intelligence in Embedded Systems;Intelligent Information Privacy Management;It's All in the Timing: Representing and Reasoning about Time in Interactive Behavior;and Linked Data Meets Artificial Intelligence. Copyright © 2010.

关键词： Embedded systems

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Beta-eigenspaces for autonomous mobile robotic trajectory outlier detection

Beta-eigenspaces for autonomous mobile robotic trajectory ou...

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IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

作者： Shyba Zaheer Tauseef Gulrez Department of Electrical Engineering College of Engineering and Applied Sciences Al Ghurair University Dubai Academic City UAE Department of Computer Science Center of Intelligent Machines & Robotics Research COMSATS Institute of Information Technology Lahore Pakistan

This paper addresses the problem of robotics trajectory building for efficient navigation and consequently exploration. A concept of beta-eigenvector has been introduced to find an outlier for the existing non-point based trajectory obtained from raw laser data. We have used our paradigm of “free configuration eigenspaces” method, with specific focus on outlier detection. The key idea proposed in this paper is to replace the Gaussian distribution utilized by the probabilistic principal component analysis (PPCA) with the beta-distribution. It is a well known issue that the conventional PCA is sensitive to anomalous observations because the calculation of sample mean and covariance matrix can be significantly influenced by a small number of outliers. Similarly, PPCA is not robust to outliers since the data are assumed to follow a multivariate Gaussian distribution that is easily affected by deviant observations. An outlier detection is done using Beta-Probabilistic Principal Component Analysis (BPPCA), further more an analysis is proposed to identify which variables contribute the most to the occurrence of outliers. The proposed technique is applied on real-time robotics sensor data as well as on the real-time robotics simulation environment.

关键词： Trajectory Principal component analysis Robot sensing systems Lasers Mobile communication Mobile robots

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