We review recent biological vision studies that are related to human motion segmentation. Our goal is to develop a practically plausible computational framework that is guided by recent cognitive and psychological studies on the human visual system for the segmentation of human body in a video sequence. Specifically, we discuss the roles and interactions of bottom-up and top-down processes in visual perception processing as well as how to combine them synergistically in one computational model to guide human motion segmentation. We also examine recent research on biological movement perception, such as neural mechanisms and functionalities for biological movement recognition and two major psychological tracking theories. We attempt to develop a comprehensive computational model that involves both bottom-up and top-down processing and is deeply inspired by biological motion perception. According to this model, object segmentation, motion estimation, and action recognition are results of recurrent feedforward (bottom-up) and feedback (top-down) processes. Some open technical questions are also raised and discussed for future research. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Cheng, C., & Guoliang, F. (2006). What can we learn from biological vision studies for human motion segmentation? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4292 LNCS-II, pp. 790–801). Springer Verlag. https://doi.org/10.1007/11919629_79
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