Recognizing dance motions with segmental SVD

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

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Detail(s)

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages1537-1540
Publication statusPublished - 2010

Publication series

Name
ISSN (Print)1051-4651

Conference

Title2010 20th International Conference on Pattern Recognition, ICPR 2010
PlaceTurkey
CityIstanbul
Period23 - 26 August 2010

Abstract

In this paper, a novel concept of segmental singular value decomposition (SegSVD) is proposed to represent a motion pattern with a hierarchical structure. The similarity measure based on the SegSVD representation is also proposed. SegSVD is capable of capturing the temporal information of the time series. It is effective in matching patterns in a time series in which the start and end points of the patterns are not known in advance. We evaluate the performance of our method on both isolated motion classification and continuous motion recognition for dance movements. Experiments show that our method outperforms existing work in terms of higher recognition accuracy. © 2010 IEEE.

Research Area(s)

  • Dance motion recognition, Segmental SVD

Citation Format(s)

Recognizing dance motions with segmental SVD. / Deng, Liqun; Leung, Howard; Gu, Naijie; Yang.

Proceedings - International Conference on Pattern Recognition. 2010. p. 1537-1540 5597020.

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