Dynamic tracking system through PSO and Parzen particle filter

Zalili Binti Musa, Junzo Watada, Sun Yan, Haochen Ding

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    Transportation plays a pivotal role in our society, especially in a good quality of life and economic prosperity. Intelligent transportation system (ITS) has been developed to manage the transport infrastructure and vehicles since the number of vehicles is rapidly growing and to avoid any accident. Various applications have provided to support ITS. One of them is a driver-assistant system. Considering of heavy vehicles such as bus, truck, trailer and etc., the driver assistant system is of importance in monitoring and recognizing objects in vehicle surrounding. For example, in operating a heavy vehicle, a driver has a limited view of the vehicle surrounding itself. It is difficult for the driver to ensure that the surrounding of vehicle is safe before operating the machine. Thus, in this paper, we employ a video tracking system through PSO and Parzen particle filter to break through several problems such as simultaneous motion and occlusion among objects. This method makes it easy to track a human movement from every frame and indirectly require less a processing time for tracking an object location in a video stream compared to conventional method. The detail outcome and result are discussed using experiments of the method in this paper.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages220-227
    Number of pages8
    Volume5712 LNAI
    EditionPART 2
    DOIs
    Publication statusPublished - 2009
    Event13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009 - Santiago
    Duration: 2009 Sep 282009 Sep 30

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume5712 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
    CitySantiago
    Period09/9/2809/9/30

    Keywords

    • Dynamic tracking system
    • Human tracking
    • Parzen particle filter
    • PSO
    • Template matching

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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