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作者： Möller, Birgit Plötz, Thomas Fink, Gernot A. Institute of Computer Science Martin-Luther-University Halle-Wittenberg Halle Germany Intelligent Systems Group Robotics Research Institute Dortmund University of Technology Dortmund Germany

ISBN: (纸本)9781424421756

Ensembles of multiple (active) cameras yield an important ingredient in modern tracking and surveillance applications. They overcome the limited fields-of-view of single cameras, however, require robust procedures for handing over tracking tasks from one camera to another. In this paper a calibration-free procedure is proposed that allows for fast and reliable camera hand-over in Ambient Intelligence (AmI) applications. The approach is based on online acquisition of scenario-specific target models and especially solves the problem of significant changes in object view during hand-over. Real-world results acquired in an AmI environment prove the effectiveness of our technique. © 2008 IEEE.

关键词： Calibration

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3D Face Tracking and Expression Inference from a 2D Sequence Using Manifold Learning

3D Face Tracking and Expression Inference from a 2D Sequence...

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26th IEEE Conference on computer Vision and Pattern Recognition (CVPR 2008), vol.11

作者： Wei-Kai Liao Gerard Medioni Computer Science Department Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

We propose a person-dependent, manifold-based approach for modeling and tracking rigid and nonrigid 3D facial deformations from a monocular video sequence. The rigid and nonrigid motions are analyzed simultaneously in 3D, by automatically fitting and tracking a set of landmarks. We do not represent all nonrigid facial deformations as a simple complex manifold, but instead decompose them on a basis of eight 1D manifolds. Each 1D manifold is learned offline from sequences of labeled expressions, such as smile, surprise, etc. Any expression is then a linear combination of values along these 8 axes, with coefficient representing the level of activation. We experimentally verify that expressions can indeed be represented this way, and that individual manifolds are indeed 1D. The manifold dimensionality estimation, manifold learning, and manifold traversal operation are all implemented in the N-D Tensor Voting framework. Using simple local operations, this framework gives an estimate of the tangent and normal spaces at every sample, and provides excellent robustness to noise and outliers. The output of our system, besides the tracked landmarks in 3D, is a labeled annotation of the expression. We demonstrate results on a number of challenging sequences.

关键词： Deformable models Active appearance model Active shape model Face detection intelligent robots Facial animation Humans Principal component analysis computer science robotics and automation

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Camera handoff with adaptive resource management for multi-camera multi-target surveillance

Camera handoff with adaptive resource management for multi-c...

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IEEE 5th International Conference on Advanced Video and Signal Based Surveillance, AVSS 2008

作者： Chen, Chung-Hao Yi, Yao Page, David Abidi, Besma Koschan, Andreas Abidi, Mongi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN 37996 United States GE Global Research Center Niskayuna NY 12309 United States

ISBN: (纸本)9780769533414

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras' resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah. © 2008 IEEE.

关键词： Cameras

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The Third International Conference on human-robot interaction

The Third International Conference on human-robot interactio...

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作者： Fong, Terry Dautenhahn, Kerstin Scheutz, Matthias Demiris, Yiannis Intelligent Robotics Group NASA Ames Research Center Department of Artificial Intelligence School of Computer Science University of Herfordshire Herfordshire United Kingdom Adaptive Systems Research Group University of Herfordshire Herfordshire United Kingdom Department of Cognitive Science Computer Science and Informatics Cognitive Science Program Indiana University Bloomington IN United States Intelligent Robotics Team Department of Electrical Engineering Imperial College London London United Kingdom

The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of the technical and social issues underlying human-robot interaction with companion and assistive robots for long-term use in everyday life and work activities. More than 250 researchers, practitioners, and exhibitors attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2009 will be held in San Diego, California, from March 11-13, 2009. Copyright © 2008, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Spatial-temporal correlatons for unsupervised action classification

Spatial-temporal correlatons for unsupervised action classif...

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2008 IEEE Workshop on Motion and Video Computing, WMVC

作者： Savarese, Silvio DelPozo, Andrey Niebles, Juan Carlos Fei-Fei, Li Beckman Institute University of Illinois Urbana Champaign IL United States Dept. of Computer Science University of Illinois Urbana-Champaign IL United States Dept. of Computer Science Princeton University United States Robotics and Intelligent Systems Group Universidad del Norte Colombia

ISBN: (纸本)1424420008

Spatial-temporal local motion features have shown promising results in complex human action classification. Most of the previous works [6],[16],[21] treat these spatial-temporal features as a bag of video words, omitting any long range, global information in either the spatial or temporal domain. Other ways of learning temporal signature of motion tend to impose a fixed trajectory of the features or parts of human body returned by tracking algorithms. This leaves little flexibility for the algorithm to learn the optimal temporal pattern describing these motions. In this paper, we propose the usage of spatial-temporal correlograms to encode flexible long range temporal information into the spatial-temporal motion features. This results into a much richer description of human actions. We then apply an unsupervised generative model to learn different classes of human actions from these ST-correlograms. KTH dataset, one of the most challenging and popular human action dataset, is used for experimental evaluation. Our algorithm achieves the highest classification accuracy reported for this dataset under an unsupervised learning scheme.

关键词： Classification (of information)

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LIDA and a theory of mind

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作者： Friedlander, David Franklin, Stan Cognitive Computing Research Group Houston TX United States Computer Science Department Institute for Intelligent Systems University of Memphis United States

ISBN: (纸本)9781586038335

Every agent aspiring to human level intelligence, every AGI agent, must be capable of a theory of mind. That is, it must be able to attribute mental states, including intentions, to other agents, and must use such attributions in its action selection process. The LIDA conceptual and computational model of cognition offers an explanation of how theory of mind is accomplished in humans and some other animals, and suggests how this explanation could be implemented computationally. Here we describe how the LIDA version of theory of mind is accomplished, and illustrate it with an example taken from an experiment with monkeys, chosen for simplicity. © 2008 The authors and IOS Press. All rights reserved.

关键词： Artificial intelligence

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Multi features models for robust lip tracking

Multi features models for robust lip tracking

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Quoc Dinh Nguyen Maurice Milgram Thi-Hoang-Lan Nguyen Institute of Intelligent Systems and Robotics University of Pierre and Marie Curie-Paris VI Paris France Department of Computer Science Hanoi University of Technology Hanoi Vietnam

We propose and evaluate a novel method for enhancing performance of lips contour tracking, which is based on the concept of statistic shape models (ASM) and multi features. On the first image of the video sequence, lip region is detected using the Bayesian's rule in which lip color information is modeled by using the Gaussian mixture model (GMM) and the GMM is trained by expectation-maximization (EM) algorithm. The lip region is then used to initialize the lip shape model. A single feature-based ASM presents good performance only in particular conditions but gets stuck in local minima for noisy conditions (like beard, wrinkle, poor texture, low contrast between lip and skin, etc). To enhance the convergence, we propose to use 2 features: normal profile and grey level patches, and combine them by using a voting approach. The standard ASM is not able to take into account temporal information from previous frames therefore the lip contours are tracked by replacing the standard ASM with a hybrid active shape model (HASM) which is capable to take advantage of the temporal information. Initial experimental results on video sequences show that MF-HASM is more robust to local minimum problem and gives a higher accuracy than traditional single feature-based method in lip tracking problem.

关键词： Robustness Shape Video sequences Lips Statistics Bayesian methods Noise shaping Skin Convergence Voting

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On the Design of Rotorcraft Landing Controllers

On the Design of Rotorcraft Landing Controllers

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2008 Mediterranean Conference on Control Automation, vol.4

作者： Pedro Serra Rita Cunha Carlos Silvestre Department of Electrical Engineering and Computer Science and Institute of Systems and Robotics Instituto Superior Technico Lisboa Portugal

This paper describes a solution to the problem of landing a helicopter autonomously. The methodology used poses the problem as a discrete time path following control problem where a conveniently defined error state space model of the helicopter is modified to include the aerodynamic effects of flying within close proximity to the ground. An affine parameter-dependent model representation is adopted that describes the helicopter linearized error dynamics for the predefined landing operating region. A state feedback H{sub}2 control problem for affine parameter-dependent systems is posed and solved using Linear Matrix Inequalities (LMIs). The resulting nonlinear controller is implemented using the D-methodology and dynamic weights to enforce bandwidth constraints on the actuators. The effectiveness of the proposed controller with and without dynamic weights on the actuation is assessed in simulation using the full nonlinear dynamic model of a small-scale helicopter.

关键词： Automation Conferences

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Multi features hybrid Active Shape Model for automated lip contours tracking in video sequence

Multi features hybrid Active Shape Model for automated lip c...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Quoc Dinh Nguyen Maurice Milgram Thi-Hoang-Lan Nguyen Institute of Intelligent Systems and Robotics ISIR-4 University of Pierre and Marie Curie-Paris VI Paris France Institute of Intelligent Systems and Robotics ISIR-4 Pierre and Marie Curie University (paris 6) Paris France Department of Computer Science Hanoi University of Technology Hanoi Vietnam

We propose and evaluate a novel method for enhancing performance of lips contour tracking, which is based on the concept of active shape models (ASM) and multi features. On the first image of the video sequence, lip region is detected using the Bayesian's rule in which lip color information is modeled by a Gaussian mixture model (GMM) which is trained by expectation-maximization (EM) algorithm. The lip region is then used to initialize the lip shape model. A single feature-based ASM presents good performance only in particular conditions but gets stuck in local minima for noisy conditions (like beard, wrinkle, poor texture, low contrast between lip and skin, etc). To enhance the convergence, we propose to use 2 features: normal profile and grey level patches, and combine them with a voting approach. The standard ASM is not able to take into account temporal information from previous frames therefore the lip contours are tracked by replacing the standard ASM with a hybrid active shape model (HASM) which is capable to take advantage of the temporal information. Initial experimental results on video sequences show that MF-HASM is more robust to local minimum problem and gives a higher accuracy than traditional single feature-based method in lip tracking problem.

关键词： Active shape model Video sequences Robustness Active appearance model Mouth Face detection intelligent robots Lips Voting Hybrid intelligent systems

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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