Vision and Learning Applied to Understanding Human Movement Vision and Learning Applied to Understanding Human Movement Brief Description of Objectives Over the last few years there has been growing recognition that 'disembodied' intelligent systems are subject to significant and systemic shortcomings. The subject of symbol grounding has received renewed focus, and the role of perceptual systems and their contribution to the overall performance of intelligent systems has been more fully appreciated.
Intelligence is, after all, a socially mediated process.
I further assume that intelligence is dependent on embodied perception, and that sensing and acting processes are unintelligible when separated. These assumptions lead me to seek close correspondence between machine vision and human vision. My specific objective is to model human perception of movement, using understanding of human movement as the specific yardstick for qualification of the vision system and, ultimately, developing a robotic implementation of the model. Mark Peters Vision and Pattern Recognition is part of the Department of Artificial Intelligence , in the School of Computer Science and Engineering , Faculty of Engineering, University of New South Wales.