DocumentCode :
2045881
Title :
An improved body action recognition method based on manifold learning
Author :
Peng Zhang ; Songmin Jia ; Tao Xu ; Xiuzhi Li ; Xuan Xuan
Author_Institution :
Coll. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing, China
fYear :
2015
fDate :
2-5 Aug. 2015
Firstpage :
1697
Lastpage :
1702
Abstract :
The body action recognition is one of the key technologies of the computer vision. As the fact that the features of body action usually reside on low dimensional manifolds embedded in a high dimensional ambient space, a new method of body action recognition based on manifold learning is proposed in this paper. In the proposed method, a Linear Local Embedding of Difference (DLLE) algorithm is applied to get the low dimensional manifolds of the images and achieve human action recognition. The result shows that the DLLE method has more advantage in time-consuming and recognition accuracy rate than the other dimensionality reduction methods. Furthermore, the experimental results demonstrated the feasibility and effectiveness of the proposed algorithm in body action recognition.
Keywords :
computer vision; learning (artificial intelligence); DLLE algorithm; body action recognition method; computer vision; high dimensional ambient space; linear local embedding of difference; manifold learning; Accuracy; Algorithm design and analysis; Feature extraction; Image reconstruction; Laplace equations; Manifolds; Principal component analysis; DLLE algorithm; body action recognition; dimensionality reduction; manifold learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-7097-1
Type :
conf
DOI :
10.1109/ICMA.2015.7237741
Filename :
7237741
Link To Document :
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