Video-based range estimation for automotive applications: Performance analysis and specification

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The research that my collaborators and I carry out is in the general area of computer vision, the attempt to endow machines with a sense of sight. From a theoretical point of view this is an important endeavor as it bears on fundamental issues in complex information processing, and may yield results that bear on our understanding of visual information processing in natural systems (e.g., humans), as well. From a practical point of view, machines that can see have the potential to interact with humans in a much more natural and useful fashion than is currently the case. The research encompassed in this particular proposal represents a collaborative effort between Canadian academia (York University) and industry (General Motors of Canada). It is concerned with rigorously characterizing the performance of video camera-based computer vision technology for estimation of relative 3D distance and direction to environmental objects from a moving vehicle. Distance and direction to environmental objects are required for collision avoidance, obstacle detection and parking. Analogous to the role of vision in human perception, video-based sensing in automobiles is anticipated to play a key role in the quest to build a human-like perception around vehicles; performance specification, as set forth in the current proposal, will be key to realizing this potential. This research contributes to Canada in three important ways. First, it will enable advanced automotive technology via incorporation of video-based sensing on next generation vehicles and thereby enhance the competitiveness of the Canadian automotive supply chain. Second, it more generally will advance the discipline of computer vision through rigorous performance evaluation of 3D distance and orientation estimation techniques and thereby pave the way for incorporation of such methods in vision machines; this allows Canada to compete successfully in a critical area of science and technology. Third, it provides students with hands on experience and skills in vital areas of investigation, computer vision and, more generally, computer science and engineering. Students go on to make careers in science, technology, teaching and elsewhere, taking with them the enrichment of having been involved in research.