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Motion Recognition based on Sparse Representation and 3D Spatial–temporal Feature

초록

영어

The emergence of a large number of databases for capturing 3D human motions has made the efficient analysis and processing of human motion data to effectively use these databases a new challenge. To reduce high-dimension complexity, a dimensional feature based on the 3D spatial–temporal characteristic should be extracted from human motions. Moreover, the motion data should be re-expressed by sparse representation to realize the projection from high dimensional data to a low-dimensional subspace. The different motions should then be recognized and classified to obtain the automatic recognition and automatic retrieval of 3D human motions.

목차

Abstract
 1. Introduction
 2. Extraction of Motion Data Features
  2.1. Calculation of Three-dimensional Space
  2.2. Sparse Representation of Motion
  2.3. Motion Recognition based on Sparse Representation
 3. Experimental Results and Analysis
 Acknowledgements
 References

저자정보

  • Jian Xiang School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China

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