Compression of human motion data sequences

Guodong Liu, Leonard McMillan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

As more and more human motion data are widely used to animate computer graphics figures in many applications, there is an imperative need to compress motion data for compact storage and fast transmission. We propose a data-driven method for efficient compression of human motion sequences by exploiting both spatial and temporal coherences of the data. We first segment a motion sequence into subsequences such that the poses within a subsequence lie near a low dimensional linear space. We then compress each segment using the principal component analysis. Further compression is achieved by storing only the key frames' projections to the principal component space and interpolating the other frames in-between the key frames via spline functions. The experimental results show that our method can achieve significant compression rate with low reconstruction errors.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006
PublisherIEEE Computer Society
Pages248-255
Number of pages8
ISBN (Print)0769528252, 9780769528250
DOIs
StatePublished - Jan 1 2006
Event3rd International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006 - Chapel Hill, NC, United States
Duration: Jun 14 2006Jun 16 2006

Publication series

NameProceedings - Third International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006

Other

Other3rd International Symposium on 3D Data Processing, Visualization, and Transmission, 3DPVT 2006
CountryUnited States
CityChapel Hill, NC
Period6/14/066/16/06

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications

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