We describe a vision-based vehicle detection and tracking method for forward collision warning in automobiles. The approach is based on a set of edge-based constraint filters that assist in the segmentation of vehicles from background clutter. The detected vehicles are then tracked using a combination of distance based matching, sum-of-square-of-difference in intensity (SSD) and edge density of detected vehicle regions. The computational load for tracking is minimized using a vehicle-clustering algorithm. Experimental results are presented to illustrate the performance of the algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vision-based vehicle detection and tracking method for forward collision warning in automobiles


    Contributors:

    Published in:

    Publication date :

    2002-01-01


    Size :

    444316 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Vision-Based Vehicle Detection and Tracking Method for Forward Collision Warning in Automobiles

    Srinivasa, N. / INRIA / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2003



    A Vision-Based Method for Vehicle Forward Collision Warning

    Zhang, Yanfei / Wang, Zhangyu / Zhou, Bin et al. | British Library Conference Proceedings | 2020


    A Fusion System for Real-Time Forward Collision Warning in Automobiles

    Srinivasa, N. / Chen, Y. / Daniell, C. et al. | British Library Conference Proceedings | 2003


    A fusion system for real-time forward collision warning in automobiles

    Srinivasa, N. / Yang Chen, / Daniell, C. | IEEE | 2003