DocumentCode
799096
Title
Documenting motion sequences with a personalized annotation system
Author
Kahol, Kanav ; Tripathi, Priyamvada ; Panchanathan, Sethuraman
Author_Institution
Arizona State Univ., USA
Volume
13
Issue
1
fYear
2006
Firstpage
37
Lastpage
45
Abstract
We present a novel technique for motion annotation that adapts to a person´s style and vocabulary of basic movements (gestures). The system segments continuous motion sequences into gestures, which it then documents in a personalized annotation with an intuitive hierarchical representation. Initial testing suggests that software based on this technique could be an effective teaching aid for dance and sports.
Keywords
humanities; image motion analysis; image segmentation; image sequences; human gestures; motion annotation; motion sequence documentation; motion sequence segmentation; personalized annotation system; Biological system modeling; Computational modeling; Computer vision; Handicapped aids; Hidden Markov models; Humans; Motion analysis; Software performance; System testing; Vocabulary; Human motion analysis and documentation; dance movement analysis;
fLanguage
English
Journal_Title
MultiMedia, IEEE
Publisher
ieee
ISSN
1070-986X
Type
jour
DOI
10.1109/MMUL.2006.5
Filename
1580432
Link To Document