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检索条件"机构=The Computer Vision And Robotics Research Laboratory"

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A Comparison of Color and Infrared Stereo Approaches to Pedestrian Detection

A Comparison of Color and Infrared Stereo Approaches to Pede...

引用

IEEE Symposium on Intelligent Vehicle

作者： Stephen J. Krotosky Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

This paper presents an analysis of color and infrared stereo approaches to pedestrian detection. We design a four camera experimental testbed consisting of two color and two infrared cameras that allows for synchronous capture and direct frame-by-frame comparison of pedestrian detection approaches. We incorporate this four camera system in a test vehicle and conduct comparative experiments of stereo-based approaches to obstacle detection using color and infrared imagery. A detailed analysis of these experiments shows the robustness of both color and infrared stereo imagery to generate the dense stereo maps necessary for robust object detection and motivates investigation of color and infrared features that can be used to further classify detected obstacles into pedestrian regions. The complementary nature of color and infrared features gives rise to a discussion of a feature fusion techniques, including a cross-spectral stereo solution to pedestrian detection.

关键词： Infrared detectors Image color analysis Cameras Infrared imaging Robustness Object detection System testing Vehicle detection Image analysis Fusion power generation

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A biologically inspired approach for the control of the hand

A biologically inspired approach for the control of the hand

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Congress on Evolutionary Computation

作者： Emmanouil Hourdakis Michail Maniadakis Panos Trahanias Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Department of Computer Science University of Crete Greece Postdoctoral researcher with the Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Head of the Computational Vision and Robotics Laboratory Foundation for Research and Technology Hellas Heraklion Greece Professor with the Department of Computer Science University of Crete Greece

The control of the hand in primate species is characterized by a high dimensionality, due to the large number of joints in the fingers. In this study we present how its manipulation can be simplified without compromising its usage, through a constraint methodology that is inspired from recent neurobiological findings. We further develop a computational model, consisting of several brain areas related to hand control, using a co-evolutionary architecture. Due to its neurobiological basis the methodology gives rise to a number of emergent properties that have been shown to occur in primate species during reach-to-grasp tasks.

关键词： Biological control systems Brain modeling computer science computer architecture Biological system modeling Computational modeling Neurons Biological neural networks computer vision Robot kinematics

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Modeling Overlapping Execution/Observation Brain Pathways

Modeling Overlapping Execution/Observation Brain Pathways

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International Joint Conference on Neural Networks (IJCNN)

作者： Michail Maniadakis Manolis Hourdakis Panos Trahanias Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas Heraklion Greece Department of Computer Science University of Crete Greece

Recent brain imaging studies on primates revealed that a network of brain areas is activated both during observation and during execution of movements. The present work aims at modeling this group of areas, implementing a distributed computational system. The modeling process follows the agent-based coevolutionary framework that is very effective in terms of designing complex distributed systems addressing successfully the multi-modality of the interacting regions. The implemented model is successfully embedded in a simulated humanoid robot, replicating existing biological findings.

关键词： Brain modeling Biological system modeling computer science Computational modeling computer architecture computer vision Robot vision systems Laboratories Humanoid robots Humans

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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...

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2006 Conference on computer vision and Pattern Recognition Workshops

作者： McCall, Joel C. Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San Diego United States

ISBN: (纸本)0769526462

In this paper we present a framework for tracking non-rigid 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. © 2006 IEEE.

关键词： Face recognition

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N-tree disjoint-set forests for maximally stable extremal regions

N-tree disjoint-set forests for maximally stable extremal re...

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2006 17th British Machine vision Conference, BMVC 2006

作者： Murphy-Chutorian, Erik Trivedi, Mohan Computer Vision and Robotics Research Laboratory University of California San Diego United States

ISBN: (纸本)1904410146

In this paper we introduce the NDS-Forest data structure, which can be used for the calculation and representation of Maximally Stable Extremal Regions in real-time video. In contrast to the standard MSER algorithm, the NDS-Forest stores information about the extremal regions as they are formed, making it unnecessary to regrow the regions from seed pixels. Using the NDS-Forest structure, we describe a system that uses MSERs in an automobile for face registration, segmentation, and pose estimation of the driver.

关键词： Forestry

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Registration of multimodal stereo images using disparity voting from correspondence windows

Registration of multimodal stereo images using disparity vot...

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IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Krotosky, Stephen Trivedi, Mohan University of California San Diego Computer Vision and Robotics Research Laboratory San Diego CA United States

ISBN: (纸本)0769526888

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. © 2006 IEEE.

关键词： computer vision

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Panoramic Appearance Map (PAM) for multi-camera based person re-identification

Panoramic Appearance Map (PAM) for multi-camera based person...

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IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Gandhi, Tarak Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San Diego San Diego CA 92093 United States

ISBN: (纸本)0769526888

This paper proposes a concept of panoramic appearance map to perform reidentification of a people who leave the scene and reappear after some time. The map is a compact signature of appearance information of a person extracted from multiple cameras. The person is detected and tracked in multiple cameras and triangulation is used to accurately localize the person in 3-D. A virtual cylinder is formed around the person's location and mapped onto an image with the horizontal axis representing the azimuth angle and vertical axis representing the height. Each bin in the map image gets the appearance information from all the cameras which can observe it. The maps between different tracks are matched using a weighted metric. Experimental results showing person matching and reidentification show the effectiveness of the approach. © 2006 IEEE.

关键词： Pattern recognition

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Multimodal voxelization and kinematically constrained Gaussian mixture models for full hand pose estimation: An integrated systems approach

Multimodal voxelization and kinematically constrained Gaussi...

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Fourth IEEE International Conference on computer vision Systems, ICVS'06

作者： Cheng, Shinko Y. Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San Diego 9500 Oilman Drive San Diego CA 92037

ISBN: (纸本)0769525067

We propose a new approach to the hand pose estimation problem using only volume information. We describe a thermal and color image-based approach to generate silhouettes of the hand with which voxel images are produced using shape-from-silhouette. We assume a 16-component, 27 degree-of-freedom kinematically constrained Gaussian mixture model, and fit it over the voxel images. We constrain the otherwise freely-arranged components of this model by a system of equations describing joint characteristics parameterized by component centroids and orientations. We use the EM algorithm and steepest descent to estimate the parameters of the model such that they yield the maximum likelihood and kinematically correct pose estimates. We demonstrate the effectiveness of the proposed system on synthesized as well as captured voxel images of the hand, and show that given appropriate initial conditions, the iterative model parameter estimation procedure effectively converges to and tracks the "voxelized" articulated hand. © 2006 IEEE.

关键词： Motion estimation

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Multimodal stereo image registration for pedestrian detection

Multimodal stereo image registration for pedestrian detectio...

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ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference

作者： Krotosky, Stephen Trivedi, Mohan Computer Vision and Robotics Research Laboratory University of California San Diego 9500 Gilman Dr. 0434 San Diego CA 92093 United States

ISBN: (纸本)1424400945

This paper presents an approach for the registration of multimodal imagery for pedestrian detection when the significant depth differences of objects in the scene precludes 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. © 2006 IEEE.

关键词： Image registration

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Human Behavior Based Predictive Brake Assistance

Human Behavior Based Predictive Brake Assistance

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IEEE Symposium on Intelligent Vehicle

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

Driver assistance systems have both the potential to alert the driver to critical situations and distract or annoy the driver if the driver is already aware of the situation. As systems attempt to preemptively warn drivers more and more in advance, this problem becomes exacerbated. We present a predictive braking assistance system that identifies not only the need for braking action, but also whether or not a braking action is being planned by the driver. Our system uses a Bayesian framework to determine the criticality of the situation by assessing (1) the probability that braking should be performed given observations of the vehicle and surround and (2) the probability that the driver intends to perform a braking action. We train and evaluate our system using over 22 hours of data collected from real driving scenarios with 28 different drivers

关键词： Humans Control systems Bayesian methods Vehicle driving Remotely operated vehicles Hidden Markov models Road accidents Programmable control Adaptive control Sensor systems

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