Low-rank based compact representation of motion capture data

Junhui Hou, Lap Pui Chau, Ying He, Nadia Magnenat-Thalmann

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

In this paper, we propose a practical, elegant and effective scheme for compact mocap data representation. Guided by our analysis of the unique properties of mocap data, the input mocap sequence is optimally segmented into a set of subsequences. Then, we project the subsequences onto a pair of computational orthogonal matrices to explore strong low-rank characteristic within and among the subsequences. The experimental results show that the proposed scheme is much more effective for reducing the data size, compared with the existing techniques.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1480-1484
Number of pages5
ISBN (Electronic)9781479957514
DOIs
Publication statusPublished - 28 Jan 2014
Externally publishedYes

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • compression
  • low-rank
  • Motion capture

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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