As digital cameras and powerful computers have become wide-spread, the number of applications using vision techniques has increased significantly. One such application that has received significant attention from the computer vision community is traffic surveillance. The authors propose a new traffic surveillance system that works without prior, explicit camera calibration, and has the ability to perform surveillance tasks in real time. Camera intrinsic parameters and its position with respect to the ground plane were derived using geometric primitives common to any traffic scene. The authors use optical flow and knowledge of camera parameters to detect the pose of a vehicle in the 3D world. This information is used in a model-based vehicle detection and classification technique employed by their traffic surveillance application. The object (vehicle) classification uses two new techniques - color contour based matching and gradient based matching. The authors' experiments on several real traffic video sequences demonstrate good results for their foreground object detection, tracking, vehicle detection and vehicle speed estimation approaches.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Efficient vehicle tracking and classification for an automated traffic surveillance system


    Contributors:


    Publication date :

    2008


    Size :

    6 Seiten, 6 Bilder, 10 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Automatic traffic surveillance system for vehicle tracking and classification

    Jun-Wei Hsieh, / Shih-Hao Yu, / Yung-Sheng Chen, et al. | IEEE | 2006


    An automated vehicle counting system for traffic surveillance

    Kunfeng Wang, / Zhenjiang Li, / Qingming Yao, et al. | IEEE | 2007


    Robust Vehicle Detection and Tracking for Traffic Surveillance

    Jung, Y.-K. / Ho, Y.-S. | British Library Conference Proceedings | 1999