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IEEE Transactions on Haptics: Editorial

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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Spatial-Temporal correlatons for unsupervised action classification

Spatial-Temporal correlatons for unsupervised action classif...

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Workshop on Motion and Video Computing

作者： Silvio Savarese Andrey DelPozo Juan Carlos Niebles Li Fei-Fei Beckman Institute University of Illinois Urbana-Champaign USA Department of Computer Science University of Illinois Urbana-Champaign USA Robotics and Intelligent Systems Group Universidad del Norte Colombia Department of Computer Science Princeton University USA

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： Humans Cameras Robustness Video sequences computer science intelligent robots Legged locomotion Feature extraction intelligent systems Trajectory

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The second international conference on Human-Robot Interaction

The second international conference on Human-Robot Interacti...

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作者： Schultz, Alan C. Breazeal, Cynthia Fong, Terry Kiesler, Sara Washington DC United States Department of Media Arts and Scienes MIT Media Lab. Intelligent Robotics Group NASA Ames Research Center Department of Computer Science and Human Computer Interaction Carnegie Mellon University Pittsburgh PA United States

The second international conference on Human-Robot Interaction (HRI-2007) was held in Arlington, Virginia, March 9-11, 2007. The theme of the conference was "Robot as Team Member" and included posters and paper presentations on teamwork, social robotics, adaptation, observation and metrics, attention, user experience, and field testing. One hundred seventy-five researchers and practitioners attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2008 will be held in Amsterdam, The Netherlands from March 12-15, 2008. Copyright © 2007, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： robotics

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Panel: Industry Relationship Development

Panel: Industry Relationship Development

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IEEE International Conference on Information Reuse and Integration (IRI)

作者： Stuart Rubin Shu-Ching Chen Susanne Bahr William A. Gruver Robert Hockett Michael Jiang Gordon K. Lee Michael Leyton June R. Massoud Mariofanna Milanova Antony Satyadas Michael Smith Daniel Yeung SPAWAR Systems Center USA Florida International University USA Florida Institute of Technology USA Emeritus of Engineering Science Intelligent Robotics Corporation-Simon Fraser University USA Cornell University USA Motorola USA San Diego State University USA Center for Discrete Mathematics & Theoretical Computer Science (DIMACS) Rutgers University USA Independent Montreal Canada University of Arkansas Little Rock USA IBM Senior Certified Executive Architect IBM Software Group USA University of California Berkeley USA Hong Kong Polytechnic University Hung Hom Hong Kong China

The purpose of the industrial panel is summarily stated as follows. This panel serves the goal of finding ways to increase industrial participation in the SMC Transaction journals. Only through industrial collaboration can the SMC society maintain financial solvency and an influx of industrial and academic minds into its constituent fields. It is our hope that the industrial panel will provide vision and direction with these ends in mind. Invitees to the panel currently serve or have served as a CEO, president, vice-president, or other ranking executive of a corporation or federal agency that has a vested interest in transitioning research; or, as a dean (any subrank), provost, president, or grant agent of an accredited North American Research University that has experience in marketing patents, or other research products such as software, etc. Several distinguished university professors have also be invited. They have special insight into technology transition, and have a track record of bringing in funding, as appropriate, publication (not necessarily extensive, which helps us to bolster our IEEE Transaction journals as one of the subjects of our planned deliberations). The panel will address, as its primary focus, how to increase the market share of our IEEE SMC Transactions (especially Part C), while maintaining or improving their quality, maintaining or improving their financial solvency, and publishing research that industry and government need done and can share in an open forum.

关键词： Industrial relations USA Councils Sliding mode control Publishing computer industry intelligent robots Competitive intelligence Service robots mathematics computer science

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A visual servoing approach for tracking features in urban areas using an autonomous helicopter

A visual servoing approach for tracking features in urban ar...

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IEEE International Conference on robotics and Automation (ICRA)

作者： L. Mejias P. Campoy S. Saripalli G.S. Sukhatme Computer Vision Group Universidad Politécnica de Madrid Madrid Spain Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

The use of unmanned aerial vehicles (UAVs) in civilian and domestic applications is highly demanding, requiring a high-level of capability from the vehicles. This work addresses the design and implementation of a vision-based feature tracker for an autonomous helicopter. Using vision in the control loop allows estimating the position and velocity of a set of features with respect to the helicopter. The helicopter is then autonomously guided to track these features (in this case windows in an urban environment) in real time. The results obtained from flight trials in a real world scenario demonstrate that the algorithm for tracking features in an urban environment, used for visual servoing of an autonomous helicopter is reliable and robust

关键词： Visual servoing Urban areas Helicopters Aircraft navigation Machine vision Control systems Unmanned aerial vehicles Global Positioning System computer vision Robot vision systems

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Towards Open Architectures for Mobile Robots: ZeeRO

Towards Open Architectures for Mobile Robots: ZeeRO

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IEEE International Conference on Automation, Quality and Testing, robotics, AQTR

作者： Radu Bogdan Rusu Radu Robotin Gheorghe Lazea Cosmin Marcu Robotics Research Group Department of Automation Technical University of Cluj Napoca Cluj-Napoca Romania Intelligent Autonomous Systems Computer Science Department Technische Universität München Munich Germany

We report on ongoing research regarding the development of open mobile robot architectures. Preliminary results of our work show that a great degree of modularity and complexity in mobile robot design can be achieved, by simply using off-the-shelf available hardware components. A hardware robotic platform would not be nearly as efficient, if it wouldn't be sustained by an adequate software system. We are proposing the use and the development of the player/stage software project, of which we are active contributors, as the backbone of our software robotic platform. This paper presents the experimental results regarding the development of the ZeeRO mobile robot, with an emphasis on its hardware and software architecture. We give insight on the structure of the main modules (navigation, sensing, processing), as well as the robot's interface with the Player server. Several tests with virtual environment navigation algorithms by means of simulation tools (Stage, Gazebo) have also been conducted. A small section of the paper is dedicated to Javaclient, a player/stage client for the Java programming language, initially developed at the University of Southern California, and later moved to SourceForge

关键词： Mobile robots Hardware Robot sensing systems Navigation Java computer architecture Software systems Spine Software architecture Testing

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Automatic distance measurement and material characterization with infrared sensors

Automatic distance measurement and material characterization...

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RoboCup 2004 Symposium

作者： Garcia, Miguel Angel Solanas, Agusti Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Av. Països Catalans 26 43007 Tarragona Spain

This paper describes a new technique for determining the distance to a planar surface and, at the same time, obtaining a characterization of the surface's material through the use of conventional, low-cost infrared sensors. The proposed technique is advantageous over previous schemes in that it does not require additional range sensors, such as ultrasound devices, nor a priori knowledge about the materials that can be encountered. Experiments with an all-terrain mobile robot equipped with a ring of infrared sensors are presented. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Sensors

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Automatic selection of multiple texture feature extraction methods for texture pattern classification

Automatic selection of multiple texture feature extraction m...

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Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005

作者： Puig, Domènec Garcia, Miguel Ángel Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Av. Paísos Catalans 26 43007 Tarragona Spain

Texture-based pixel classification has been traditionally carried out by applying texture feature extraction methods that belong to a same family (e.g., Gabor filters). However, recent work has shown that such classification tasks can be significantly improved if multiple texture methods from different families are properly integrated. In this line, this paper proposes a new selection scheme that automatically determines a subset of those methods whose integration produces classification results similar to those obtained by integrating all the available methods but at a lower computational cost. Experiments with real complex images show that the proposed selection scheme achieves better results than well-known feature selection algorithms, and that the final classifier outperforms recognized texture classifiers. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Fetal monitoring

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Automatic classification of breast density

Automatic classification of breast density

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IEEE International Conference on Image Processing

作者： A. Oliver J. Freixenet R. Zwiggelaar Computer Vision and Robotics Group University of Girona Girona Spain Department of Computer Science University of Wales Aberystwyth UK

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques.

关键词： Breast cancer Mammography computer aided diagnosis Image segmentation Lesions computer vision Robot vision systems robotics and automation computer science Data mining

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Multi-view face detection based on real Adaboost algorithm

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Jisuanji Yanjiu yu Fazhan/computer Research and Development 2005年第9期42卷 1612-1621页

作者： Wu, Bo Huang, Chang Ai, Haizhou Lao, Shihong State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China Sensing Technology Laboratory Vision Sensing Technology Group Omron Corporation Kyoto 619-0283 Japan

In this paper, a multi-view face detection method based on real Adaboost algorithm is presented. Human faces are divided into several viewpoint categories according to their poses in 3D, and for each of these categories a form of weak classifiers in look-up-table (LUT) type is designed using Haar-like features that have confidences in real values as their outputs, and correspondingly its space of weak classifiers is constructed, from which the cascade face detector is learnt by using real Adaboost algorithm. For speed up, multi-resolution searching and pose prediction strategies are introduced. For frontal face detection, the experiments on CMU + MIT frontal face test set result in a correct rate of 94.5% with 57 false alarms;for multi-view face detection, the experiments on CMU profile face test set result in a correct rate of 89.8% with 221 false alarms. The average processing time on a PIV 2.4 GHz PC is about 80 ms for a 320 × 240-pixel image. It can be seen that the proposed method is very efficient and has significant value in application.

关键词： Haar-like feature LUT weak classifier Multi-view face detection Pose estimation Real Adaboost

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