Abstract
2/2013
vol. 30
Original paper
3D HUMAN MOTION RETRIEVAL BASED ON
HUMAN HIERARCHICAL INDEX STRUCTURE
Biol. Sport 2013;30:145-151
Online publish date: 2014/07/22
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.
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.
Keywords
motion capture, human hierarchical structure, motion pattern, KMP algorithm, motion retrieval
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