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REAL-TIME vision BASED AUV NAVIGATION SYSTEM USING A COMPLEMENTARY SENSOR SUITE

IFAC Proceedings Volumes 2007年第17期40卷 373-378页

作者： Jonathan Horgan Daniel Toal Pere Ridao Rafael Garcia Mobile and Marine Robotics Research Centre Department of Electronic and Computer Engineering University of Limerick Ireland Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Spain

This paper proposes a real-time navigation system for an AUV that takes advantage of the complementary performance of a sensor suite including a DVL, a compass, a depth sensor and altimeter sensors with a feature based motion estimator using vision. To allow for real-time performance of the vision based motion estimator a simple but fast correlation algorithm is used for feature matching. The compass and the depth sensors are used to bound the drift of the heading and depth estimations respectively. The altimeter is required in order to translate the feature displacements measured from the images into the metric displacements of the robot. While the robot must rely on DVL navigation above a certain altitude where vision is useless, DVL measurements can be complemented with higher frequency accurate motion estimates from the vision system when navigating close to the seafloor.

关键词： marine robotics robot vision Kalman filtering robot navigation

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Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation

Head Pose Estimation for Driver Assistance Systems: A Robust...

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International Conference on Intelligent Transportation

作者： Erik Murphy-Chutorian Anup Doshi Mohan Manubhai Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

Recognizing driver awareness is an important prerequisite for the design of advanced automotive safety systems. Since visual attention is constrained to a driver's field of view, knowing where a driver is looking provides useful cues about his activity and awareness of the environment. This work presents an identity-and lighting-invariant system to estimate a driver's head pose. The system is fully autonomous and operates online in daytime and nighttime driving conditions, using a monocular video camera sensitive to visible and near-infrared light. We investigate the limitations of alternative systems when operated in a moving vehicle and compare our approach, which integrates Localized Gradient Orientation histograms with support vector machines for regression. We estimate the orientation of the driver's head in two degrees-of-freedom and evaluate the accuracy of our method in a vehicular testbed equipped with a cinematic motion capture system.

关键词： Robustness Magnetic heads Automotive engineering Safety Cameras Remotely operated vehicles Histograms Support vector machines Motion estimation System testing

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Video Based Surround Vehicle Detection, Classification and Logging from Moving Platforms: Issues and Approaches

Video Based Surround Vehicle Detection, Classification and L...

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IEEE Symposium on Intelligent Vehicle

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

This paper discusses the issues and approaches involved in developing a mobile vehicle-mounted system to detect, classify, and log the surrounding vehicles in a database for efficient query-based retrieval. This system consists of three components: (1) vehicle sensing, detection, and tracking (2) feature extraction and classification (3) database storage and retrieval. Relevant research in each of these components is described in order to guide the development of such a system. Such a system has applications including traffic analysis from mobile probes, analyzing driver behavior based on surrounding vehicles, as well as surveillance from mobile platform.

关键词： Vehicle detection Cameras Road vehicles Information retrieval Image sensors Vehicle driving Object detection Monitoring Layout Laser radar

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A Two-stage Multi-view Analysis Framework for Human Activity and Interactions

A Two-stage Multi-view Analysis Framework for Human Activity...

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Workshop on Motion and Video Computing

作者： Sangho Park Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

ISBN: (纸本)9781424431366;9780769527932

This paper presents a new framework for a multi-stage multi-view approach for human interactions and activity analysis. The analysis is performed in a distributed vision system that synergistically integrate track- and body-level representations across multiple cameras. Our system aims at versatile and easily-deployable system that does not require careful camera calibration. Main contributions of the paper are: (1) context-dependent camera handover for occlusion handling, (2) switching the multi-stage analysis between track- and body-level representations, and (3) a hypothesis-verification paradigm for top-down feedback exploiting spatio-temporal constraints inherent in human interaction. Experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions. Current implementation uses two views, but extension to more views is straightforward.

关键词： Humans Cameras computer vision Condition monitoring Robot vision systems Machine vision Feedback Motion analysis computerized monitoring Image analysis

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Homography-based Analysis of People and Vehicle Activities in Crowded Scenes

Homography-based Analysis of People and Vehicle Activities i...

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IEEE Workshop on Applications of computer vision (WACV)

作者： Sangho Park Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

This paper presents an new framework for homography-based analysis of pedestrian-vehicle activity in crowded scenes. Planar homography constraint is exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatio-temporal relationships between people- and vehicle- tracks are represented by a semantic event. Context awareness of the situation is achieved by the estimated density distribution of objects and the anticipation of possible directions of near-future tracks using piecewise velocity history. Single-view and multi-view based homography mapping options are compared. Our framework can be used to enhance situational awareness for disaster prevention, human interactions in structured environments, and crowd movement analysis at wide regions

关键词： Vehicles Layout Surveillance Humans computer vision Cameras Robot vision systems Safety Transmission line matrix methods Feature extraction

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Real-Time Video Based Highway Traffic Measurement and Performance Monitoring

Real-Time Video Based Highway Traffic Measurement and Perfor...

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International Conference on Intelligent Transportation

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

This paper presents a real-time highway monitoring system for tracking and classification of vehicles with the computation of traffic flow parameters from live video streams. The proposed system robustly detects and tracks vehicles during daylight hours and accurately classifies them into 8 different types by leveraging tracking information. The system is able to process video continuously over long time periods, accumulating large volumes of tracking data to build daily highway models consisting of the traffic flow parameters, density, flow, and speed. These daily models are used to categorize the speed profile of live traffic.

关键词： Road transportation Traffic control Detectors Vehicle detection Road vehicles Object detection Event detection Real time systems Condition monitoring computer vision

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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...

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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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