title: 3d human motion retrieval based on human hierarchical index structure.
abstract: With the development and wide application of motion capture technology, the captured motion data sets are becoming larger and larger. For this reason, an efficient retrieval method for the motion database is very important. The retrieval method needs an appropriate indexing scheme and an effective similarity measure that can organize the existing motion data well. In this paper, we represent a human motion hierarchical index structure and adopt a nonlinear method to segment motion sequences. Based on this, we extract motion patterns and then we employ a fast similarity measure algorithm for motion pattern similarity computation to efficiently retrieve motion sequences. The experiment results show that the approach proposed in our paper is effective and efficient.
authors.affiliation: Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, Ministry of Education, Dalian, China.
authors.forename: Q
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, Ministry of Education, Dalian, China.
authors.forename: X
authors.initials: X
authors.lastname: Guo
keywords: KMP algorithm; human hierarchical structure; motion capture; motion pattern; motion retrieval
references.citation: IEEE Trans Inf Technol Biomed. 2009 Sep;13(5):802-9
references.pmid: 19403368