|
UWSpace >
University of Waterloo >
Electronic Theses and Dissertations (UW) >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10012/3468
|
| Title: | Vehicle Tracking in Occlusion and Clutter |
| Authors: | McBride, Kurtis |
| Keywords: | Tracking
MCMC |
| Approved Date: | 8-Jan-2008 |
| Date Submitted: | 2007 |
| Abstract: | 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 an
unknown number of targets and the variations in real-world lighting, scene conditions and camera vantage. Scene clutter and target
occlusion 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 are
presented which show that the framework is capable of tracking vehicles in scenes containing multiple vehicles that occlude one
another, and that are occluded by foreground scene objects. |
| Program: | System Design Engineering |
| Department: | Systems Design Engineering |
| Degree: | Master of Applied Science |
| URI: | http://hdl.handle.net/10012/3468 |
| Appears in Collections: | Faculty of Engineering Theses and Dissertations
Electronic Theses and Dissertations (UW)
|
This item is protected by original copyright
|
All items in UWSpace are protected by copyright, with all rights reserved.
|
