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Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis (Foundations and Trends(R) in Computer Graphics and Vision(R))

معرفی کتاب «Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis (Foundations and Trends(R) in Computer Graphics and Vision(R))» نوشتهٔ David A. Forsyth; Okan Arikan; Leslie Ikemoto; James O'Brien; Deva Ramanan در سال 2005. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.

Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis reviews methods for kinematic tracking of the human body in video. The review confines itself to the earlier stages of motion, focusing on tracking and motion synthesis. There is an extensive discussion of open issues. The authors identify some puzzling phenomena associated with the choice of human motion representation --- joint angles vs. joint positions. The review concludes with a quick guide to resources and an extensive bibliography of over 400 references. Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis is an invaluable reference for those engaged in computational geometry, computer graphics, image processing, imaging in general, and robotic. We review methods for kinematic tracking of the human body in video. The review is part of a projected book that is intended to cross-fertilize ideas about motion representation between the animation and computer vision communities. The review confines itself to the earlier stages of motion, focusing on tracking and motion synthesis; future material will cover activity representation and motion generation. In general, we take the position that tracking does not necessarily involve (as is usually thought) complex multimodal inference problems. Instead, there are two key problems, both easy to state. The first is lifting, where one must infer the configuration of the body in three dimensions from image data. Ambiguities in lifting can result in multimodal inference problem, and we review what little is known about the extent to which a lift is ambiguous. The second is data association, where one must determine which pixels in an image come from the body. We see a tracking by detection approach as the most productive, and review various human detection methods Originally published as Foundations and trends in computer graphics and vision, v. 1, issue 2/3 (2005).
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