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Human Animation from 2D Correspondence Based on Motion Trend Prediction

  • Li Zhang
  • Ling Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4035)

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.

Keywords

Human Motion Computer Animation Human Posture Rotational Acceleration Rotation Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li Zhang
    • 1
  • Ling Li
    • 1
  1. 1.Department of ComputingCurtin University of TechnologyPerthAustralia

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