Vehicle Tracking in Occlusion and Clutter

Tracking;MCMC;System Design Engineering

McBride, Kurtis

University of Waterloo

关键词: Tracking;    MCMC;    System Design Engineering;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/3468/1/Thesis.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Vehicle tracking in environments containing occlusion and clutter is an active research area.The problem of tracking vehicles through such environments presents a variety of challenges. These challenges include vehicle track initialization, tracking anunknown number of targets and the variations in real-world lighting, scene conditions and camera vantage. Scene clutter and targetocclusion present additional challenges. A stochastic framework is proposed which allows for vehicles tracks to be identified from a sequence of images. The work focuses on the identification of vehicle tracks present in transportation scenes, namely, vehicle movements at intersections. The framework combines background subtraction and motion history based approaches to deal with the segmentation problem. The tracking problem is solved using a Monte Carlo Markov Chain Data Association (MCMCDA) method. The method includes a novel concept of including the notion of discrete, independent regions in the MCMC scoring function. Results arepresented which show that the framework is capable of tracking vehicles in scenes containing multiple vehicles that occlude oneanother, and that are occluded by foreground scene objects.