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A multimodal framework for vehicle and traffic flow analysis

A multimodal framework for vehicle and traffic flow analysis

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International Conference on Intelligent Transportation

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

This paper presents an overview of a novel multimodal system being developed at UC San Diego for vehicle detection and traffic flow analysis. A distributed multimodal array (DiMMA) framework is presented for sensory data acquisition, processing, analysis, fusion, and "active" control mechanisms needed to recognize objects, events, and activities which have multi-modal signatures. Current sensing modalities being researched include video, audio, seismic, magnetic, and passive infrared. Feature extraction and data fusion techniques are being investigated to improve robustness and study the advantages and disadvantages of each sensing modality. Preliminary results of this rapidly deployable system are discussed, along with possible future expansions, including laser range scanners, geophones, pneumatic road tubes, and traditional inductive loops

关键词： Vehicle detection Road vehicles Monitoring Robustness Sensor arrays Magnetic analysis Traffic control Information security Detectors Cameras

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Dynamic Panoramic Surround Map: Motivation and Omni Video Based Approach

Dynamic Panoramic Surround Map: Motivation and Omni Video Ba...

引用

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

作者： T. Gandhi M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

Awareness of what surrounds a vehicle directly affects the safe driving and maneuvering of an automobile. Surround information or maps can help in ethnographic studies of driver behavior as well as provide a critical input in the development of effective driver assistance system. In this paper, we introduce the concept of Dynamic Panoramic Surround (DPS) map that shows the nearby surroundings of the vehicle, and detects the objects of importance on the road. Omnidirectional cameras which give a panoramic view of the surroundings can be useful for visualizing and analyzing the nearby surroundings of the vehicle. A novel approach for synthesizing the DPS using stereo and motion analysis of video images from a pair of omni-directional cameras on the vehicle is developed. Successful generation of DPS in experimental runs on an instrumented vehicle testbed is demonstrated. These experiments prove the basic feasibility and show promise of omni video based DPS capture algorithm to provide useful semantic descriptors of the state of moving vehicles and obstacles in the vicinity of a vehicle.

关键词： Vehicle dynamics Vehicle detection Cameras Vehicle driving Vehicle safety Automobiles Road vehicles Object detection Visualization Motion analysis

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Looking-in and looking-out of a vehicle: selected investigations in computer vision based enhanced vehicle safety

Looking-in and looking-out of a vehicle: selected investigat...

引用

IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： M.M. Trivedi T. Gandhi J. McCall Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

This paper presents an overview of investigations into the role of computer vision technology in developing safer automobiles. We consider vision systems which cannot only look out of the vehicle to detect and track roads, avoid hitting obstacles or pedestrian, but simultaneously look inside the vehicle to monitor the attentiveness of the driver and even predict her intentions. In this paper, a systems-oriented framework for developing computer vision technology for safer automobiles is presented. We will consider three main components of the system, driver, vehicle, and vehicle surround. We will discuss various issues and ideas for developing models for these main components as well as activities associated with the complex task of safe driving. The paper includes discussion of novel sensory systems and algorithms for capturing not only the dynamic surround information of the vehicle but also the state, intent and activity patterns of drivers.

关键词： Vehicle safety computer vision Vehicle driving Road vehicles Vehicle dynamics Automobiles Cameras Laboratories Machine vision Vehicle detection

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A track-based human movement analysis and privacy protection system adaptive to environmental contexts

A track-based human movement analysis and privacy protection...

引用

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

作者： Sangho Park M.M. Trivedi Computer Vision and Robotics Research (CVRR) Laboratory University of California San Diego La Jolla CA USA

This paper presents a track-based system for human movement analysis and privacy protection. Our system is adaptive to environmental contexts such as illumination variations, complex moving cast shadows, different camera perspectives, and diverse sue scenarios. Most of outdoor surveillance systems have been targeting at specific environmental situation: i.e., specific time, place, and activity scenarios. We address that more general human movement analysis systems should be able to handle multiple heterogeneous situations in an adaptive manner. We introduce the concept of "spatio-temporal personal boundary" to represent different grouping patterns of human tracks, and we incorporate the concept with various site models. Experimental evaluations with extensive outdoor data show our system's robustness to environmental changes and effectiveness to properly handle various environmental contexts.

关键词： Privacy Protection Adaptive systems Biomedical monitoring Humans Surveillance Layout Robot vision systems Target tracking Cameras

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Multiperspective Thermal IR and Video Arrays for 3D Body Tracking and Driver Activity Analysis

Multiperspective Thermal IR and Video Arrays for 3D Body Tra...

引用

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

作者： Shinko Y. Cheng Sangho Park M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA

This paper presents a multi-perspective (i.e., four camera views) multi-modal (i.e., thermal infrared and color) video based system for robust and real-time 3D tracking of important body *** multi-perspective characteristics of the system provides 3Dtrajectory of the body parts, while the multi-modal characteristics of the system provides robustness and reliability of feature detection and tracking. The application context for this research is that of intelligent vehicles and driver assistance systems. Experimental results demonstrate effectiveness of the proposed system.

关键词： Cameras computer vision Infrared detectors Humans Head Robustness Robot vision systems Image color analysis Real time systems Intelligent vehicles

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Vehicle wheel detector using 2D filter banks

Vehicle wheel detector using 2D filter banks

引用

IEEE Symposium on Intelligent Vehicle

作者： O. Achler M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

Detecting vehicles from a moving vehicle is an important task. In this paper a new vehicle detector is introduced. The new vehicle detector employs the use of the ubiquitous wheel. Every car has wheels; this wheel detector finds wheels and infers vehicle location from the wheel detection. Views from an omnidirectional camera are used to generate side view images. These images are processed using a difference of Gaussian filter bank. The responses from the filter bank are applied to a precomputed set of principle components. The principle component responses are compared against a Gaussian mixture model of wheels and Gaussian model roadbed. Wheel candidates are chosen and tracked. Initial experimental results along with analysis are shown.

关键词： Vehicle detection Wheels Detectors Channel bank filters Vehicles Cameras Roads Principal component analysis Vehicle driving Filter bank

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Camera based vehicle detection, tracking, and wheel baseline estimation approach

Camera based vehicle detection, tracking, and wheel baseline...

引用

International Conference on Intelligent Transportation

作者： O. Achler M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

Detecting and classifying vehicles using a stationary camera is an important task in intelligent transportation systems. A novel vehicle detector is introduced. The vehicle detector uses the most common feature among all vehicles, the ubiquitous wheel. The vehicle detector finds wheels and infers vehicle location from background segmentation and wheel detection. Views from a rigid rectilinear camera are used. The images are convolved using a difference of Gaussian filterbank. The responses from the filterbank are applied to a precomputed set of principle components. The principle component responses are compared against a Gaussian mixture model of wheels and Gaussian mixture model of non-wheels. Wheel candidates are chosen and tracked. Any wheel tracked in the foreground is chosen as wheel. Initial experimental results along with analysis are included.

关键词： Cameras Vehicle detection Wheels Vehicles Detectors Robot vision systems Bridges Subtraction techniques Intelligent robots Intelligent transportation systems

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Occupant posture analysis using reflectance and stereo image for "smart" airbag deployment

Occupant posture analysis using reflectance and stereo image...

引用

IEEE Symposium on Intelligent Vehicle

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

Robust detection of vehicle occupant posture is necessary for intelligent airbag deployment. This paper presents a vision-based method of estimating the size, posture and pose of the occupant. Utilizing raw reflectance and stereo disparity images, this algorithm presents a mixed-mode approach to finding occupant features. Extensive experiments show the viability of this mixed-mode method in identifying the occupant's head location and suggest the feasibility of extending the analysis system to include detection of features such as occupant arms and foreign objects.

关键词： Image analysis Reflectivity Stereo vision Head Lighting computer vision Robot vision systems Intelligent robots Laboratories Vehicle detection

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Enhancement for face video from omni-directional video camera

Enhancement for face video from omni-directional video camer...

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Asilomar Conference on Signals, Systems & computers

作者： Junwen Wu M.M. Trivedi Computer Vision and Robotics Research lab ECE Department University of California San Diego La Jolla CA USA

In this paper we propose a novel algorithm to enhance the face video from omni-directional video camera. A two-stage strategy is used. First stage is the noise elimination, realized by iterative MAP update. Naive Bayesian criterion is used to model the posterior. The predominant salt and pepper noise introduced by the omni-to-perspective transformation can be removed effectively, while the image details are well preserved. The high frequency component compensation (HFCC) super-resolution algorithm is applied thereafter to remove the blocky effect. Experimental results show that the video quality has a marked improvement.

关键词： Cameras Iterative algorithms Statistics Robot vision systems Bayesian methods Face detection Image resolution Image enhancement Streaming media Image segmentation

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A collaborative approach for human-centered driver assistance systems

A collaborative approach for human-centered driver assistanc...

引用

International Conference on Intelligent Transportation

作者： J.C. McCall O. Achler M.M. Trivedi J.-B. Haue P. Fastrez D. Forster J.D. Hollan E. Boer Computer Vision and Robotics Research Laboratory Distributed Cognition and Human Computer Interaction Laboratory University of California San Diego USA ERB Consulting and Cal-IT University of California San Diego La Jolla CA USA

This paper describes an interdisciplinary research collaboration to design a human-centered driver assistance system. Driving behavior is captured using a novel intelligent vehicle test bed. The synchronized capture o... 详细信息

关键词： Collaboration Vehicle driving Cognition Streaming media Laboratories Intelligent vehicles Intelligent systems System testing Data analysis Video compression

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