Data parallelization is an important method for speed up the vision based vehicle recognition system. And with the risen of multi/many cores, new programmability has been introduced to extend its ability to express more complicated and irregular algorithm utilizing multi/many cores hardware, this paper presents our study on data parallel computation model and illustrates our prime data parallel optimization for the key algorithms of vision based vehicle recognition algorithm including image filters, classifier and motion estimation. And after analyzing the result of optimization, the applicably bound of data parallel optimization and the future direction of parallel optimization for vision based vehicle recognition algorithm is summarized.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Study on Data Parallel Optimization for Real-time Vehicle Recognition Algorithm


    Contributors:
    Yang, Chunyang (author) / Wen, Xuezhi (author) / Yuan, Huai (author) / Duan, Bobo (author)


    Publication date :

    2007-09-01


    Size :

    465212 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Parallelism Analysis Pattern for Real-time Vehicle Recognition Algorithm

    Yang, Chunyang / Yuan, Huai / Wang, Nan et al. | IEEE | 2007


    A Parallelism Analysis Pattern for Real-time Vehicle Recognition Algorithm

    Yang, C. / Yuan, H. / Wang, N. et al. | British Library Conference Proceedings | 2007


    A 2DLDA Based Algorithm for Real Time Vehicle Type Recognition

    Huang, Hua / Zhao, Qian / Jia, Yulan et al. | IEEE | 2008


    Real Time Vehicle Recognition

    Houghton, A / Seed, N L. / Smith, R W. M. | SPIE | 1988


    An active multiobjective real-time vibration control algorithm for parallel hybrid electric vehicle

    Song, Dafeng / Wu, Jiajun / Yang, Dongpo et al. | SAGE Publications | 2023