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access icon free Dezert–Smarandache theory for multiple targets tracking in natural environment

  • Author(s): Yi Wang 1 ; Yingwu Fang 1 ; Jian Zhang 1 ; Pengyang Li 2
    • View affiliations
    • Affiliations: 1: School of Information and Navigation, Air Force Engineering University, Fenghao Road 1, Xi'an 710077, People's Republic of China;
      2: School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, People's Republic of China
  • Source: Volume 7, Issue 6, December 2013, p. 456 – 466
    DOI:  10.1049/iet-cvi.2012.0193 , Print ISSN 1751-9632, Online ISSN 1751-9640
© The Institution of Engineering and Technology
Received 04/09/2012, Accepted 18/03/2013, Revised 15/03/2013, Published

The aim of this article was to investigate multiple targets tracking in natural environment based on Dezert–Smarandache theory (DSmT). On the basis of establishing conflict strategy and combination model, the basic framework and algorithm of fusing multi-source information were described. The multiple targets tracking platform which embedded location and colour cues into the particle filters (PFs) was developed in the framework of DSmT. Three sets of experiments with comparisons were carried out to validate the suggested tracking approach. Results showed that the conflict strategy and DSmT combination model were available, and the introduced approach exhibited a significantly better performance for dealing with high conflict between evidences than a PF. As a result, the approach was suitable for real-time video-based targets tracking, and it had the ability to track interesting targets. Furthermore, the approach can easily be generalised to deal with larger number of targets and additional cues in a complicated environment.

Inspec keywords: image colour analysis; particle filtering (numerical methods); video signals; target tracking

Other keywords: real-time video-based target tracking; colour cues; particle filters; multiple-target tracking; Dezert–Smarandache theory; combination model; multisource information fusion; natural environment; DSmT combination model

Subjects: Optical, image and video signal processing; Filtering methods in signal processing; Video signal processing

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