Low-rank based compact representation of motion capture data

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

5 Scopus Citations
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Author(s)

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

Detail(s)

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

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.

Research Area(s)

  • compression, low-rank, Motion capture

Citation Format(s)

Low-rank based compact representation of motion capture data. / Hou, Junhui; Chau, Lap-Pui; He, Ying; Magnenat-Thalmann, Nadia.

2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1480-1484 7025296.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review