Title :
Co-evolutionary-based active contour models in tracking of moving obstacles
Author :
Ooi, C. ; Liatsis, P.
Author_Institution :
UMIST, UK
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;
Conference_Titel :
Advanced Driver Assistance Systems, 2001. ADAS. International Conference on (IEE Conf. Publ. No. 483)
Conference_Location :
Birmingham
Print_ISBN :
0-85296-743-8
DOI :
10.1049/cp:20010499