Adaptive Self-Occlusion Behavior Recognition Based on pLSA
Joint Authors
Tan, Lun-zheng
Tu, Hong-bin
Xia, Li-min
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Human action recognition is an important area of human action recognition research.
Focusing on the problem of self-occlusion in the field of human action recognition, a new adaptive occlusion state behavior recognition approach was presented based on Markov random field and probabilistic Latent Semantic Analysis (pLSA).
Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms an occlusion state variable by phase space obtained.
Then, we proposed a hierarchical area variety model.
Finally, we use the topic model of pLSA to recognize the human behavior.
Experiments were performed on the KTH, Weizmann, and Humaneva dataset to test and evaluate the proposed method.
The compared experiment results showed that what the proposed method can achieve was more effective than the compared methods.
American Psychological Association (APA)
Tu, Hong-bin& Xia, Li-min& Tan, Lun-zheng. 2013. Adaptive Self-Occlusion Behavior Recognition Based on pLSA. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-477076
Modern Language Association (MLA)
Tu, Hong-bin…[et al.]. Adaptive Self-Occlusion Behavior Recognition Based on pLSA. Journal of Applied Mathematics No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-477076
American Medical Association (AMA)
Tu, Hong-bin& Xia, Li-min& Tan, Lun-zheng. Adaptive Self-Occlusion Behavior Recognition Based on pLSA. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-477076
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-477076