• DocumentCode
    2204060
  • Title

    Co-evolutionary-based active contour models in tracking of moving obstacles

  • Author

    Ooi, C. ; Liatsis, P.

  • Author_Institution
    UMIST, UK
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    58
  • Lastpage
    62
  • Abstract
    A new symbiotic genetic algorithm (SGA)-based active contour model (Snake) is proposed to track the B-spline contour of obstacles. It exploits the local control properties of the B-spline to decompose the contour into subcontours and optimizes each subcontour in separate genetic algorithms (GA). Unlike GA-based Snake, a SGASnake can track the obstacles outline more robustly. Application-specific inter-population genetic operators are introduced to reinforce the symbiotic relationship via migration of genetic material. The use of symbiosis dramatically reduces the combinatorics of the search space, when compared to GA. Results of tracking objects in real road scenarios demonstrate its robustness to noise and stability of convergence when compared to its GA counterpart
  • Keywords
    combinatorial mathematics; genetic algorithms; numerical stability; road traffic; search problems; splines (mathematics); tracking; traffic engineering computing; B-spline; GA; SGASnake; active contour model; co-evolutionary-based models; inter-population genetic operators; local control properties; moving obstacle tracking; optimization; road traffic engineering; search space combinatorics; stability convergence; subcontours; symbiosis; symbiotic genetic algorithm;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Advanced Driver Assistance Systems, 2001. ADAS. International Conference on (IEE Conf. Publ. No. 483)
  • Conference_Location
    Birmingham
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-743-8
  • Type

    conf

  • DOI
    10.1049/cp:20010499
  • Filename
    981404