Spatiotemporal stereo vision for space and terrestrial robotics

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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 (MDA). It is concerned with recovering three-dimensional models of the environment from binocular (paired) video cameras. We consider binocular cameras as, similar to the two-eyed design of humans and other animals, the afforded multiple views provide a principled geometric approach to recovering three-dimensional structure of the environment. We consider video as it allows the cameras to sweep out wide area coverage and to capture dynamic aspects of the environment. This research contributes to Canada in three important ways. First, it advances the discipline of computer vision as we expose basic properties of image information and develop corresponding algorithms for incorporation into vision machines; this allows Canada to compete successfully in a critical area of science and technology. Second, it provides students with hands on experience and skills in vital areas of investigation, computer vision and, more generally, computer science. Students go on to make careers in science, technology, teaching and elsewhere, taking with them the enrichment of having been involved in research. Third, it paves the way for novel ways to practically exploit image data. Applications of interest include personal hand-held 3D modelers, real-time robotics for space and terrestrial deployment and automated vehicle navigation.