Monocular reconstruction of human translation in motion sequence by MTA
Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Human animation from 2D correspondence based on motion trend prediction
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Human animation from 2d correspondence based on motion trend prediction
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
Towards robust 3d reconstruction of human motion from monocular video
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
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This paper proposed an optimization approach for human motion recovery from the un-calibrated monocular images containing unlimited human movements. A 3D skeleton human model based on anatomy knowledge is employed with encoded biomechanical constraints for the joints. Energy Function is defined to represent the deviations between projection features and extracted image features. Reconstruction procedure is developed to adjust joints and segments of the human body into their proper positions. Genetic Algorithms are adopted to find the optimal solution effectively in the high dimensional parameter space by simultaneously considering all the parameters of the human model. The experimental results are analysed by Deviation Penalty. Copyright © 2004 John Wiley & Sons, Ltd.