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

Author

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

Author_Institution

Coll. of Electr. & Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China

fYear

2014

fDate

18-20 Aug. 2014

Firstpage

526

Lastpage

528

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

Markov processes; feature extraction; image recognition; random processes; video signal processing; video surveillance; Markov random field energy; feature extraction; group abnormal behavior recognition; intelligence video surveillance; pattern recognition; video images; Computational modeling; Educational institutions; Feature extraction; Hidden Markov models; Markov random fields; Streaming media; Video surveillance; Markov model; abnormal behaviors; pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics & Cognitive Computing (ICCI*CC), 2014 IEEE 13th International Conference on

Conference_Location

London

Print_ISBN

978-1-4799-6080-4

Type

conf

DOI

10.1109/ICCI-CC.2014.6921511

Filename

6921511