Compression of Human Motion Capture Data Using Motion Pattern Indexing

In this work, a novel scheme is proposed to compress human motion capture data based on hierarchical structure construction and motion pattern indexing. For a given sequence of 3D motion capture data of human body, the 3D markers are first organized into a hierarchy where each node corresponds to a...

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Bibliographic Details
Published in:Computer graphics forum Vol. 28; no. 1; pp. 1 - 12
Main Authors: Gu, Qin, Peng, Jingliang, Deng, Zhigang
Format: Journal Article
Language:English
Published: Oxford, UK Blackwell Publishing Ltd 01.03.2009
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ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary:In this work, a novel scheme is proposed to compress human motion capture data based on hierarchical structure construction and motion pattern indexing. For a given sequence of 3D motion capture data of human body, the 3D markers are first organized into a hierarchy where each node corresponds to a meaningful part of the human body. Then, the motion sequence corresponding to each body part is coded separately. Based on the observation that there is a high degree of spatial and temporal correlation among the 3D marker positions, we strive to identify motion patterns that form a database for each meaningful body part. Thereafter, a sequence of motion capture data can be efficiently represented as a series of motion pattern indices. As a result, higher compression ratio has been achieved when compared with the prior art, especially for long sequences of motion capture data with repetitive motion styles. Another distinction of this work is that it provides means for flexible and intuitive global and local distortion controls.
Bibliography:ark:/67375/WNG-L8J7H6WF-0
istex:9FF008DE9011289C4F840AB59B1C89C35660FB12
ArticleID:CGF1309
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/j.1467-8659.2008.01309.x