Human animation from 2d correspondence based on motion trend prediction

Authors:
Li Zhang;Ling Li
Affiliations:
Department of Computing, Curtin University of Technology, Perth, WA, Australia;Department of Computing, Curtin University of Technology, Perth, WA, Australia
Venue:
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
Year:
2006

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Abstract

A model-based method is proposed in this paper for 3-dimensional human motion recovery, taking un-calibrated monocular data as input. This method is designed to recover smooth human motions with high efficiency, while its outputs are guaranteed to resemble the original motion not only from the same viewpoint the sequence was taken, but also look natural and reasonable from any other viewpoint. The proposed method is called “Motion trend prediction (MTP)”. To evaluate the accuracy of the MTP, it is first tested on some “synthesized” input. After that experiments are conducted on real video data, which demonstrate that the proposed method is able to recover smooth human motions from their 2D image features with high accuracy.