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检索条件"机构=Computer Vision and Robotics"

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Biomimetic Centering for Undulatory Robots

Biomimetic Centering for Undulatory Robots

引用

IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： M. Sfakiotakis D.P. Tsakiris A. Vlaikidis Computational Vision and Robotics Laboratory Institute of Computer Science FORTH Heraklion Greece

Substantial work exists in the undulatory robotics literature on the mechanical design, modeling, gait generation and implementation of robotic prototypes. However, there appears to have been relatively limited work on the use of exteroceptive sensors in control schemes leading to more complex reactive undulatory behaviors. This paper considers a biologically-inspired sensor-based centering behavior for undulatory robots, originally developed for nonholonomic mobile robots. Adaptation to the significantly more complex dynamics of undulatory locomotors highlights a number of issues related to the use of sensors (possibly distributed over the elongated body of the mechanism) for the generation of reactive behaviors, to biomimetic neuromuscular control and to formation control of multi-undulatory swarms. These issues are explored via computational tools specifically geared towards undulatory locomotion in robotics and biology

关键词： Biomimetics Robot sensing systems Biosensors Mobile robots Biological system modeling Prototypes Mechanical sensors Neuromuscular Biology computing Computational biology

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Facial Action Coding Using Multiple Visual Cues and a Hierarchy of Particle Filters

Facial Action Coding Using Multiple Visual Cues and a Hierar...

引用

IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： J.C. McCall M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

In this paper we present a framework for tracking nonrigid facial landmarks by combining various visual cues at multiple levels of detail. Using a probabilistic framework consisting of a hierarchy of particle filters, we are able to track individual facial landmarks using multiple visual cues at the local level, as well as tracking results at more coarse level of detail. This allows for the fusion of global and local cues in an efficient and robust manner. Testing is performed by tracking and classifying facial action codes obtained from the Cohn-Kanade AU-Coded Facial Expression Database.

关键词： Particle filters Face detection Robustness Particle tracking computer vision Intelligent vehicles Humans Magnetic heads Filtering Robot vision systems

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Multimodal Stereo Image Registration for Pedestrian Detection

Multimodal Stereo Image Registration for Pedestrian Detectio...

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International Conference on Intelligent Transportation

作者： S. Krotosky M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

This paper presents an approach for the registration of multimodal imagery for pedestrian detection when the significant depth differences of objects in the scene preclude a global alignment assumption. Using maximization-of-mutual-information matching techniques and sliding correspondence windows over calibrated image pairs, we demonstrate successful registration of color and thermal data. We develop a robust method using disparity voting for determining the registration of each object in the scene and provide a statistically based measure for evaluating the match confidence. Testing shows successful registration in complex scenes with multiple people at different depths and levels of occlusion

关键词： Image registration Layout Cameras Image color analysis Image analysis Voting Robustness Infrared imaging Infrared detectors Information analysis

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Selecting and Evaluating Combinatorial Fusion Criteria to Improve Multitarget Tracking

Selecting and Evaluating Combinatorial Fusion Criteria to Im...

引用

International Conference on Information Fusion

作者： D. Frank Hsu Damian M. Lyons Jizhou Ai Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

ISBN: (纸本)1424409535

In many useful video tracking situations, targets move through repeated mutual occlusions. As targets undergo occlusions, the feature subsets and combinations of those features that are effective in identifying the target and improving tracking performance may change. We use combinatorial fusion analysis to select and evaluate criteria by which to identify the combination of features that will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results from three diverse video sequences to illustrate the performance of the proposed criteria

关键词： Target tracking Target recognition Humans Hidden Markov models computer vision Video sequences Layout Performance analysis Diversity reception Shape

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Combinatorial Fusion Criteria for Real-Time Tracking

Combinatorial Fusion Criteria for Real-Time Tracking

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International Conference on Advanced Information Networking and Applications (AINA)

作者： D.F. Hsu D.M. Lyons J. Ai Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

We address the problem of automated video tracking of targets when targets undergo multiple mutual occlusions. Our approach is based on the idea that as targets are occluded, selection of feature subsets and combinations of those features are effective in identifying the target and improving tracking performance. We use combinatorial fusion analysis to develop a metric to select which subset of features will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results to illustrate the performance of the proposed metric

关键词： Target tracking Target recognition computer vision robotics and automation Diversity reception Robot vision systems Laboratories Information science Surveillance Robot sensing systems

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PRIM an Open Mobile Robot Platform. Motivation, Present and Future Trends

PRIM an Open Mobile Robot Platform. Motivation, Present and ...

引用

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

作者： Lluis Pacheco Joan Batlle Xavier Cuff Roger Arbuse Computer Vision and Robotics Group Technical School University of Girona Girona Spain Computer Vision and Robotics Group Technical School Girona Spain Tech. Sch. Girona Univ.

This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot

关键词： Mobile robots Educational robots Education Educational institutions Multimedia systems Navigation Sensor fusion Machine vision Robot sensing systems Robot vision systems

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Stereo Matching with Symmetric Cost Functions

Stereo Matching with Symmetric Cost Functions

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Kuk-Jin Yoon In So Kweon Robotics and Computer Vision Laboratory Department Electrical Engineering and Computer Science KAIST Daejeon South Korea

Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various techniques. However, most global methods mainly focus on how to minimize conventional cost functions efficiently, although it is more important to define cost functions well to improve performance. In this paper, we propose new symmetric cost functions for global stereo methods. We first present a symmetric data cost function for the likelihood and then propose a symmetric discontinuity cost function for the prior in the MRF model for stereo. In defining cost function, both the reference image and the target image are taken into account to improve performance without modeling half-occluded pixels explicitly and without using color segmentation. The performance improvement of stereo matching due to the proposed symmetric cost functions is verified by applying the proposed symmetric cost functions to the belief propagation (BP) based stereo method. Experimental results for standard testbed images show that the performance of the BP based stereo method is greatly improved by the proposed symmetric cost functions.

关键词： Cost function Stereo vision Pixel computer vision Markov random fields Optimization methods Image segmentation Belief propagation Robot vision systems computer science

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Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

Improving Clustering Algorithms for Image Segmentation using...

引用

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

作者： Arnau Oliver Xavier Munoz Joan Batlle Lluis Pacheco Jordi Freixenet Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

关键词： Clustering algorithms Image segmentation Partitioning algorithms Proposals Clustering methods computer vision Robot kinematics Robot vision systems Informatics Application software

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Registration of Multimodal Stereo Images Using Disparity Voting from Correspondence Windows

Registration of Multimodal Stereo Images Using Disparity Vot...

引用

IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Stephen Krotosky Mohan Trivedi Computer Vision and Robotics Research LaboratoryLa Jolla University of California San Diego CA USA

This paper presents a method for registering multimodal imagery in short range surveillance situations when the differences in object depths preclude any global registration techniques. An analysis of multimodal registration approaches gives insight into the limitations of global assumptions and motivates the developed algorithm. Using calibrated stereo imagery, we use maximization of mutual information in sliding correspondence windows that inform a disparity voting scheme to demonstrate successful registration of color and thermal images. Extensive testing of scenes with multiple people at different depths and levels of occlusion shows high rates of successful registration and gives a reliable framework for further processing and analysis of the multimodal imagery.

关键词： Voting Cameras Layout Surveillance Mutual information Image registration Stereo vision Image analysis Information analysis Object detection

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Visual Modules for Head Gesture Analysis in Intelligent Vehicle Systems

Visual Modules for Head Gesture Analysis in Intelligent Vehi...

引用

IEEE Symposium on Intelligent Vehicle

作者： Junwen Wu M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego CA USA

In this paper a coarse-to-fine system framework for analyzing the head gesture is presented. We discuss several important modules from computer vision aspects, including the pose-invariant face detection, face tracking, pose determination and high-resolution image reconstruction for eye pupils detection. Visual cues using intensity images obtained from in-car cameras are explored. A pose-invariant face detection algorithm is used to get the initial face area; afterwards face tracking and validation step is proposed to segment the face region for pose determination. The algorithm is tested on the drivers images under natural driving conditions. Experimental results show that the algorithm is robust to the head pose changes as well as the illumination changes. In this system framework, we propose that when coarse analysis utilizing the head pose alone is not sufficient for driver's behavior analysis, a finer analysis based on the eye gaze tracking is used, which requires images with sufficient resolution. A novel super-resolution reconstruction algorithm is proposed to help reveal more facial details, so as to facilitate the pupil detection. Experiment on the synthesis data shows the effectiveness of the super-resolution reconstruction algorithm

关键词： Intelligent vehicles Face detection Head Image analysis Reconstruction algorithms computer vision Image reconstruction Cameras Image segmentation Testing

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