A pattern recognition for group abnormal behaviors based on Markov Random Fields energy

Li, Zuojin; Chen, Liukui; Ren, Zhiyong; Tirumala, Sreenivas Sremath

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Date
2014-08
Citation:
Li, Z.J., Chen, L.K., Ren, Z.Y. & Tirumala, S.S. (2014). A pattern recognition for group abnormal behaviors based on Markov Random Fields energy. IEEE(Ed.), IEEE 13th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2014 (pp.526-528).
Permanent link to Research Bank record:
https://hdl.handle.net/10652/3965
Abstract
Group abnormal behaviors often occur abruptly under video surveillance, thus bringing serious consequences. How to recognize these behaviors correctly has always been the difficulty in research on intelligence video surveillance. This paper is based on the basic theory of Markov Random Fields to extract the features of those in video images, so as to recognize the group abnormal behaviors under video surveillance. Experiments show that this method can well reflect the real situation at the spot.
Keywords:
computer vision, Markov Random Fields, video surveillance, human activity recognition, group abnormal behaviors, intelligent surveillance
ANZSRC Field of Research:
080109 Pattern Recognition and Data Mining
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