DocumentCode :
1626472
Title :
Recognizing human actions using histogram of local binary patterns
Author :
Ahsan, Sk Md Masudul ; Joo Kooi Tan ; Hyoungseop Kim ; Ishikawa, Seiichiro
Author_Institution :
Control Eng. Dept., Kyushu Inst. of Technol., Kitakyushu, Japan
fYear :
2013
Firstpage :
54
Lastpage :
59
Abstract :
Human action recognition from video clips has become an active research field in recent years. Each action has its unique shape and a motion sequence can be suitably represented by a histogram. In this paper a histogram based action recognition method is presented. Motion history images are a good spatiotemporal template for action representation. In the present method, we use local binary patterns of directional motion history images for the histogram representation. We measured the performance of the proposed method along with some variants of it by employing KTH action dataset and found higher accuracy. The presented results also justify the superiority of the proposed method compared to other approaches for action recognition found in literature.
Keywords :
image motion analysis; image representation; image sequences; object recognition; video signal processing; KTH action dataset; action representation; directional motion history images; histogram representation; human action recognition; local binary pattern histogram; motion sequence; spatiotemporal template; video clips; Computer vision; Histograms; Image motion analysis; Optical imaging; Support vector machines; Training; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Integration (SII), 2013 IEEE/SICE International Symposium on
Conference_Location :
Kobe
Type :
conf
DOI :
10.1109/SII.2013.6776623
Filename :
6776623
Link To Document :
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