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检索条件"机构=Computer Vision and Robotics Laboratory Computer Vision and Robotics Laboratory"

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Time perception in shaping cognitive neurodynamics of artificial agents

Time perception in shaping cognitive neurodynamics of artifi...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Michail Maniadakis Jun Tani Panos Trahanias Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas Crete Greece Laboratory for Behavior and Dynamic Cognition RIKEN Brain Science Institute Wako Saitama Japan

Recent research in cognitive systems aims to uncover important aspects of biological cognitive processes and additionally formulate design principles for implementing artificially intelligent systems. Despite the increasing amount of research efforts addressing cognitive phenomena, the issue of time perception and how it is linked to other cognitive processes remains largely unexplored. In the current paper, we make a first attempt for studying artificial time perception by means of simulated robotic experiments. Specifically, we investigate a behavioral rule switching task consisting of repeating trials with dynamic temporal duration. An evolutionary process is used to search for neuronal mechanisms accomplishing the rule switching task taking also into account its particular temporal characteristics. Our repeated simulation experiments showed that (i) time perception and ordinary cognitive processes may co-exist in the system sharing the same neural resources, and (ii) time perception dynamics bias the functionality of neural mechanisms with other cognitive responsibilities. Finally, in the current paper we make contact of the obtained results with previous brain imaging studies on time perception, and we make predictions for possible time-related dynamics in the real brain.

关键词： Neurodynamics Cognitive robotics Intelligent robots Intelligent systems Computational and artificial intelligence Robot vision systems Laboratories Brain modeling Humans computer vision

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Soft-tissue modeling and image-guided control of steerable needles

Soft-tissue modeling and image-guided control of steerable n...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Nasser Sadati Meysam Torabi Reza Vaziri Reza Dehestani-Ardekani Electrical and Computer Engineering Department University of British Columbia Vancouver BC Canada Robotics and Machine Vision Laboratory Biomedical Engineering Division of the School of Electrical Engineering Sharif University of Technology Tehran Iran

In this paper, we exploit a fuzzy controller on a flexible bevel-tip needle to manipulate the needle's base in order to steer its tip in a preset obstacle-free and target-tracking path. Although the needle tends to follow a curvature path, spinning the needle with an extremely high rotational velocity makes it symmetric with respect to the tissue to follow a straight path. The fuzzy controller determines an appropriate spinning to generate the planned trajectory and, the closed-loop system tries to match the needle body with that trajectory. The swine's brain tissue model, extracted from an in-vitro experimental setup, is a non-homogenous, uncertain and fast-updatable network to model real tissues, needle and their interactions providing the essential visual feedback for the control system. The simulation results illustrate a precise path tracking of the bevel-tip needle based on the fuzzy controller's commands with two degrees of freedom.

关键词： Needles Fuzzy control Minimally invasive surgery Brain modeling Spinning Surges Manipulator dynamics Force feedback Intelligent robots Biomedical engineering

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A coordination mechanism for swarm navigation: Experiments and analysis

A coordination mechanism for swarm navigation: Experiments a...

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7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008

作者： Marcolino, Leandro Soriano Chaimowicz, Luiz VeRLab-Vision and Robotics Laboratory Computer Science Department UFMG Brazil

ISBN: (纸本)9781605604701

We present an algorithm that allows swarms of robots to navigate in environments containing unknown obstacles, moving towards and spreading along 2D shapes given by implicit functions. Basically, a gradient descent approach augmented with local obstacle avoidance is used to control the swarm. To deal with local minima regions, we use a coordination mechanism that reallocates some robots as "rescuers" and sends them to help other robots that may be trapped. The main objective of this paper is to analyze the performance of this algorithm in terms of its completion rate and communication requirements as the number of robots increases. For this, a series of simulations are presented and discussed. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Autonomous agents

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Efficient background modeling through incremental Support Vector Data Description

Efficient background modeling through incremental Support Ve...

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作者： Tavakkoli, Alireza Nicolescu, Mircea Bebis, George Nicolescu, Monica Computer Vision Laboratory University of Nevada Reno United States Robotics Laboratory University of Nevada Reno United States

ISBN: (纸本)9781424421756

Background modeling is an essential and important part of many high-level video processing applications. Recently, the Support Vector Data Description (SVDD) has been introduced for novelty detection when only one class of data is available, i.e. background pixels. This paper proposes a method to efficiently train an SVDD and compares the performance of this training algorithm with the traditional SVDD training techniques. We compare the performance of our method with traditional SVDD and other classification algorithms on various data sets including real video sequences. © 2008 IEEE.

关键词： Data description

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Applications of High Precision Imaging Polarimetry

Applications of High Precision Imaging Polarimetry

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4th International Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging, CAe 2008

作者： Neumann, L. Hegedus, R. Horvath, G. Garcia, R. Computer Vision and Robotics Group University of Girona Icrea Spain Department of Biological Physics Biooptics Laboratory Eötvös University Budapest Hungary Computer Vision and Robotics Group University of Girona Spain

ISBN: (纸本)9783905674088

We propose the use of imaging polarimetry for general photography, which is a relatively young technique allowing the determination of polarized components of the light coming from extended objects or scenes. In this paper high resolution and accurate methods are introduced to determine the two linearly polarized components (Q;U) of light. The CIE Luv color space is used in this work to visualize the triplet of (I;Q;U) polarization image components. The structure of this color space is also highly appropriate to represent other attributes of linearly polarized light, such as the polarized intensity, degree and the angle of polarization. The accurately measured polarization components can also be efficiently used for image enhancement. In this direction, a new, polarization-based de-reflection method is proposed. This method is an optimal pixel-wise extension of the widely used photographical polarization filtering. Our method is also capable of amplifying the specular effects. Another application is de-hazing, which removes the linearly polarized component of the haze present in natural scenes, and results in a sharp and color-corrected image. Furthermore, the different combinations of visible and infrared polarization channels enable great possibilities in further de-hazing and to create artistic images. © The Eurographics Association 2008.

关键词： Image enhancement

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An adaptive scene description for activity analysis in surveillance video

An adaptive scene description for activity analysis in surve...

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作者： Morris, Brendan Trivedi, Mohan Computer Vision and Robotics Research Laboratory University of California San Diego San Diego CA 92093-0434 United States

ISBN: (纸本)9781424421756

This paper presents an adaptive framework for live video analysis. The activities of surveillance subjects are described using a spatio-temporal vocabulary learned from recurrent motion patterns. The repetitive nature of object trajectories are used to build a topographical map, where nodes are points of interest and the edges correspond to activities, to describe a scene. The graph is learned in an unsupervised manner but is flexible and able to adjust to changes in the environment or other scene variations. © 2008 IEEE.

关键词： Security systems

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Learning and classification of trajectories in dynamic scenes: A general framework for live video analysis

Learning and classification of trajectories in dynamic scene...

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

作者： Morris, Brendan T. Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA 92093-0434 United States

ISBN: (纸本)9780769533414

This paper presents a general framework for live video analysis. The activities of surveillance subjects are described using a spatio-temporal vocabulary learned from recurrent motion patterns. The repetitive nature of object trajectories is used to build a topographical scene description where nodes are points of interest (POI) and the edges correspond to activity paths (AP). The POI are learned through as a mixture of Gaussians and AP by clustering trajectories. The paths are probabilistically represented by hidden Markov models and adapt to temporal variations using online maximum likelihood regression (MLLR) and through a periodic batch update. Using the scene graph, new trajectories can be analyzed in online fashion to categorize past and present activity, predict future behavior, and detect abnormalities. ©2008 IEEE.

关键词： Trajectories

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On the problem of determination of spring stiffness parameters for spring-mesh models

On the problem of determination of spring stiffness paramete...

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Medicine Meets Virtual Reality 16 - Parallel, Combinatorial, Convergent: NextMed by Design, MMVR 2008

作者： Quang Huy Viet, Huynh Hirai, Shinichi Shirai, Yoshiaki Yamaguchi, Satoshi Tanaka, Hiromi T. Kawasaki, Hiroshi Kawai, Yukiko Computer Vision and Graphics Laboratory Department of Information and Computer Science Saitama University Saitama Japan Laboratory for Integrated Machine Intelligence Department of Robotics Ritsumeikan University Kusatsu Japan Computer Vision Lab. Department of Human and Computer Intelligence Ritsumeikan University Kusatsu Japan Kawai Lab. Department of Computer Science Kyoto Sangyo University Kyoto Japan

ISBN: (纸本)9781586038229

On account of having real-time behavior and being easy to implement, spring meshes have been used for modeling deformable objects. Determining spring stiffness parameters for simulation of soft objects with high accuracy still remains a challenge. Allen Van Gelder derived an approximate formula for determining spring stiffness parameters based on strain analysis. Even though the experimental result showed the effectiveness, the method has not been investigated from a quantitative point of view. In this paper we propose a quantitative method for determining spring stiffness parameters. Moreover we propose a method to improve the accuracy by way of introducing torsional spring into the conventional spring mesh model. © 2008 The authors. All rights reserved.

关键词： Stiffness matrix

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Efficient background modeling through incremental Support Vector Data Description

Efficient background modeling through incremental Support Ve...

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International Conference on Pattern Recognition

作者： Alireza Tavakkoli Mircea Nicolescu George Bebis Monica Nicolescu Computer Vision Laboratory University of Nevada Reno Robotics Laboratory University of Nevada Reno

ISBN: (纸本)9781424421749

关键词： Quadratic programming Kernel Laboratories Lagrangian functions computer vision Application software Classification algorithms Video sequences Robots Object detection

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Human body modelling and tracking using volumetric representation: Selected recent studies and possibilities for extensions

Human body modelling and tracking using volumetric represent...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Cuong Tran Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

Articulated human body modeling and tracking from vision data is an attractive research area with many potential applications. There has been a tremendous amount of related research works in this area. Therefore, having a comprehensive insight into high quality existing works and awareness of the research frontier in the area is essential for follow-up research studies. With that objective, this paper provides a review of the subarea of model based methods for human body modeling and tracking using volumetric (voxel) data. We will focus on analyzing and comparing some recent techniques, especially which are in the past two years, in order to highlight trends in the domain as well as to point out limitations of the current state of the art. Based on this analysis, we will discuss our idea of combining Laplacian Eigenspace (LE) based voxel segmentation [20] and Kinematically Constrained Gaussian mixture model (KC-GMM) method [3] to have a more powerful human body pose estimation system as well as discuss other possibilities for future work.

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