Date of Award
2007
Degree Type
Thesis
Degree Name
Master of Science
Program
Computer Science
Supervisor
Dr. Steven Beauchemin
Abstract
Studies conducted on motor vehicle drivers indicate that drivers from varying demographics are confronted by difficult driving contexts such as negotiating intersections, yielding, merging and overtaking. This research is based on the hypothesis that visual search patterns of at-risk drivers provide vital information required for assessing driving abilities and improving the skills of such drivers under varying conditions. We aim to detect and track the face and eyes of the driver during several driving scenarios, allowing for further processing of a driver’s visual search pattern behavior. The idea of any integrated framework employing multiple trackers is advantageous in forming a globally strong tracking methodology. In order to model the effectiveness of a tracker, a confidence parameter is introduced to help minimize the errors produced by incorrect matches and allow more effective trackers with a higher confidence value to correct the perceived position of the target.
Recommended Citation
Hamshari, Hussein O., "Computer Vision System for Facial Feature Detection and Tracking" (2007). Digitized Theses. 5004.
https://ir.lib.uwo.ca/digitizedtheses/5004