Recognition of Human Actions using an Optimal Control Based Motor Model | IEEE Conference Publication | IEEE Xplore

Recognition of Human Actions using an Optimal Control Based Motor Model

Publisher: IEEE

Abstract:

We present a novel approach to the problem of representation and recognition of human actions, that uses an optimal control based model to connect the high-level goals of...View more

Abstract:

We present a novel approach to the problem of representation and recognition of human actions, that uses an optimal control based model to connect the high-level goals of a human subject to the low-level movement trajectories captured by a computer vision system. These models quantify the high-level goals as a performance criterion or cost function which the human sensorimotor system optimizes by picking the control strategy that achieves the best possible performance. We show that the human body can be modeled as a hybrid linear system that can operate in one of several possible modes, where each mode corresponds to a particular high-level goal or cost function. The problem of action recognition, then is to infer the current mode of the system from observations of the movement trajectory. We demonstrate our approach on 3D visual data of human arm motion.
Date of Conference: 07-09 January 2008
Date Added to IEEE Xplore: 17 June 2008
ISBN Information:
Print ISSN: 1550-5790
Publisher: IEEE
Conference Location: Copper Mountain, CO, USA

References

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