Document Detail

Adaptive Motion Data Representation with Repeated Motion Analysis.
MedLine Citation:
PMID:  20530815     Owner:  NLM     Status:  Publisher    
In this paper, we present a representation method for motion capture data by exploiting the nearly repeated characteristics and spatio-temporal coherence in human motion. We extract similar motion clips of variable lengths or speeds across the database. Since the coding costs between these matched clips are small, we propose the repeated motion analysis to extract the refered and repeated clip pairs with maximum compression gains. For further utilization of motion coherence, we approximate the subspace-projected clip motions or residuals by interpolated functions with range-aware adaptive quantization. Our experiments demonstrate that the proposed feature-aware method is of high computational efficiency. Furthermore, it also provides substantial compression gains with comparable reconstruction and perceptual errors.
I-Chen Lin; Jen-Yu Peng; Chao-Chih Lin; Ming-Han Tsai
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2010-6-3
Journal Detail:
Title:  IEEE transactions on visualization and computer graphics     Volume:  -     ISSN:  1077-2626     ISO Abbreviation:  -     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-6-9     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9891704     Medline TA:  IEEE Trans Vis Comput Graph     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
National Chiao Tung University, Hsinchu City.
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