[1]MEI Xue,HU Shi,XU Songsong,et al.Multi scale feature based double layer HMM and its application in behavior recognition[J].CAAI Transactions on Intelligent Systems,2012,7(6):512-517.
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Multi scale feature based double layer HMM and its application in behavior recognition

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 6 Page number: 512-517 Column: 学术论文—机器感知与模式识别 Public date: 2012-12-25
Title:
Multi scale feature based double layer HMM and its application in behavior recognition
Author(s):
MEI Xue;  HU Shi;  XU Songsong;  ZHANG Jifa
College of Automation and Electrical Engineering, Nanjing University of Technology, Nanjing 211816, China
Keywords:
doublelayer HMM (DLHMM);  behavior recognition;  multiscale feature;  intelligent video surveillance
CLC:
TP391.4
DOI:
-
Abstract:
Learning from multiscale and multidistinguish attributes of human beings’ visual perception and aiming at human movement behavior recognition in intelligent video surveillance system, a doublelayer hidden markov model (DLHMM) is developed based on multiscale behavior features. Considering the human behavior characteristics, the number of HMM states is according to the number of key gestures selected. Discovering the relationship between the multiscale structures hidden in the human movement behavior, two different scale featureshuman motion trajectory and wavelet moment of human gesture’s edge, are applied respectively in two layers of DLHMM, so as to provide more scale information about behavior. Experiments, using Israel Weizmann human behavior database and human actions indoor recorded by ourselves, show the fivestate HMM more accords with the human motion behavior characteristics, and the fivestate DLHMM based on multiscale feature has a higher recognition rate compared with traditional methods using one layer HMM.
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