DocumentCode :
248421
Title :
Graph-based approach for motion capture data representation and analysis
Author :
Jiun-Yu Kao ; Ortega, Antonio ; Narayanan, Shrikanth S.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
2061
Lastpage :
2065
Abstract :
Providing better representation methods for motion capture data can lead to improved performance in terms of classification, recognition, synthesis and dimensionality reduction. In this paper, we propose a novel representation method inspired by algebraic and spectral graph theoretic concepts. Our proposed method represents motion data in a space constructed with bases for skeleton-like graphs. We introduce two criteria and as well as its influences on the generated bases. With experiments on CMU MoCap database, we will also discuss how this method may act as a good preprocessing tool in order to enhance the further analysis steps on MoCap data.
Keywords :
data analysis; data reduction; data structures; graph theory; image motion analysis; CMU MoCap database; algebraic graph theoretic concept; dimensionality reduction; gait analysis; graph-based approach; motion capture data analysis; motion capture data representation; skeleton-like graphs; spectral graph theoretic concept; Databases; Joints; Laplace equations; Legged locomotion; Principal component analysis; Vectors; Human motion; dimensionality reduction; gait analysis; graph-based approach; motion capture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025413
Filename :
7025413
Link To Document :
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