Title :
Documenting motion sequences with a personalized annotation system
Author :
Kahol, Kanav ; Tripathi, Priyamvada ; Panchanathan, Sethuraman
Author_Institution :
Arizona State Univ., USA
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;
Journal_Title :
MultiMedia, IEEE
DOI :
10.1109/MMUL.2006.5
