Michael Black's research addresses estimation and understanding of human movement. His group has been developing computational and mathematical models of movement that can be recovered from video sequences using new computer vision algorithms. At the core of this work are probabilistic models of the visual world that are learned from natural scenes. Furthermore, his group exploits these models of human movement in the design of neural motor prosetheses. In particular they model the relationship between neural firing activity of populations of motor cortical neurons and complex natural movement. The goal is to enable paralyzed patients to control dexterous robot hands using neural signals recorded with an implanted electrode array.
Michael Black received his B.Sc. from the University of British
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Michael J. Black
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