Extraction of Primitive Motion and Discovery of Association Rules from Human Motion Data

Abstract

In the past several years, human motion data has been used in some domains such as SFX movies, CGs and so on. Motion data is captured by a motion capture system which captures the position of sensors on body joints, so we can get motion data as 3-D time series data. Since, motion data is multi-stream data of time series for 17 body parts, the amount of data is huge. Furthermore, motion data is expensive. A motion database can help those creators to produce motion data with less cost. The database, however, requires a content-based retrieval method because it is difficult to identify the motion by using a keyword approach. Consequently we introduce association rules which represent dependency between body parts. Association rules represent the motion of body parts and can be used as visual tags. We introduce a method to discover dependency between body parts as association rules. Association rules consist of symbols uniquely representing basic patterns. We call basic patterns primitive motions. Primitive motions are extracted from motion data by using segmentation and clustering processes. Finally, we discuss some experiments to discover association rules from multi-streams of motion data.