2P2-Q09 Motion Data Retrieval Based on Statistic Correlation between Motion Symbols Space and Language(Informative Motion & Motion Media)
Seiya Hamano, Wataru Takano, Yoshihiko Nakamura · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2011
This paper proposes motion retrieval method based on stochastic correlation between motion and language. We construct Word-Proto-Symbol Space which has maximum correlation with motion pattern features and word features, and we use this space as search space for motion retrieval. Proto-Symbol Space, which represents relationship of each symbolized motion patterns, is used as motion feature space. And as word feature, binary features are used which represent whether a word label is attached or not. Because Word Proto-Symbol Space has correlation between motion patterns and words, associative motion retrieval considering similarity of motion pattern or closeness of word meaning becomes possible. We validate proposed motion retrieval method by constructing motion database with captured human motion data.