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    Non-overlapping Distributed Tracking System Utilizing Particle Filter

    117805.pdf (1.157Mb)
    Access Status
    Open access
    Authors
    Lim, Fee Lee
    Leoputra, Wilson
    Tan, Tele
    Date
    2007
    Type
    Journal Article
    
    Metadata
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    Citation
    Lim, Fee Lee and Leoputra, Wilson and Tan, Tele. 2007. Non-overlapping distributed tracking system utilizing particle filter. The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology. 49 (3): pp. 343-362.
    Source Title
    The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology
    DOI
    10.1007/s11265-007-0091-4
    ISSN
    09225773
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/41093
    Collection
    • Curtin Research Publications
    Abstract

    Tracking people across multiple cameras is a challenging research area in visual computing, especially when these cameras have non-overlapping field of views. The important task is to associate a current subject with other prior appearances of the same subject across time and space in a camera network. Several known techniques rely on Bayesian approaches to perform the matching task. However, these approaches do not scale well when the dimension of the problem increases; e.g. when the number of subject or possible path increases. The aim of this paper is to propose a unified tracking framework using particle filters to efficiently switch between visual tracking (field of view tracking) and track prediction (non-overlapping region tracking). The particle filter tracking system utilizes a map (known environment) to assist the tracking process when targets leave the field of view of any camera. We implemented and tested this tracking approach in an in-house multiple cameras system as well as using on-line data. Promising results were obtained which suggested the feasibility of such an approach.

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