NDLI: Body Motion Analysis for Similarity Retrieval of Motion Data and Its Evaluation

Content Provider	IEEE Xplore Digital Library
Author	Woong Choi Ono, T. Hachimura, K.
Copyright Year	2009
Abstract	With the spread of motion capture systems, body motion data has been obtained without effort and quantity of its data has been increasing. We need an efficient method for target motion retrieval. In this paper, we propose the method of analyzing motion data in advance, and express the construction of movement with indexed labels for reducing similar-motion retrieval. The posture of each frame is distinguished into the pattern of the indexed labels, and we therefore try to index each motion data. Firstly, we reduce the number of dimensions of motion data with PCA (Principal Components Analysis) and do clustering. Next, a trained dictionary is consisted of the indexed motion data. Finally, SVM (Support Vector Machine) distinguishes the test data by using the dictionary. In this research, we made the trained dictionary from the movement of radio gymnastics, and then carried out an evaluation of discrimination by using break dance movement as test data. As a result, we could use the motion data with indexes, and obtained a good retrieval result in this experiment.
Starting Page	1177
Ending Page	1180
File Size	597967
Page Count	4
File Format	PDF
ISBN	9781424447176
DOI	10.1109/IIH-MSP.2009.174
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-12
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Dictionaries Multimedia systems Information retrieval Machine Learning Support vector machines Signal processing Similarity Retrieval Motion analysis Principal component analysis Testing Gravity Motion Data
Content Type	Text
Resource Type	Article

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