A pattern recognition for group abnormal behaviors based on Markov Random Fields energy
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Other Title
Authors
Li, Zuojin
Chen, Liukui
Ren, Zhiyong
Tirumala, Sreenivas Sremath
Chen, Liukui
Ren, Zhiyong
Tirumala, Sreenivas Sremath
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2014-08
Supervisors
Type
Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
computer vision
Markov Random Fields
video surveillance
human activity recognition
group abnormal behaviors
intelligent surveillance
Markov Random Fields
video surveillance
human activity recognition
group abnormal behaviors
intelligent surveillance
ANZSRC Field of Research Code (2020)
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).
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.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Permanent link
Link to ePress publication
DOI
DOI: 10.1109/ICCI-CC.2014.6921511
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