Abnormal event detection based on analysis of movement information of video sequence

Abnormal event detection based on analysis of movement information of video sequence

Abnormal event detection is a challenging problem in video surveillance which is essential to the early-warning security and protection system. We propose an algorithm to solve this problem efficiently based on an image descriptor which encodes the movement information and the classification method....

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Veröffentlicht in:Optik (Stuttgart) 2018-01, Vol.152, p.50-60
Hauptverfasser: Wang, Tian, Qiao, Meina, Deng, Yingjun, Zhou, Yi, Wang, Huan, Lyu, Qi, Snoussi, Hichem
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Abnormal event detection
Engineering Sciences
Hidden Markov model
Optical flow
Signal and Image processing
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container_end_page 60
container_issue
container_start_page 50
container_title Optik (Stuttgart)
container_volume 152
creator Wang, Tian
Qiao, Meina
Deng, Yingjun
Zhou, Yi
Wang, Huan
Lyu, Qi
Snoussi, Hichem
description Abnormal event detection is a challenging problem in video surveillance which is essential to the early-warning security and protection system. We propose an algorithm to solve this problem efficiently based on an image descriptor which encodes the movement information and the classification method. The new abnormality indicator is derived from the hidden Markov model which learns the histograms of optical flow orientations of the observed video frames. This indicator measures the similarity between the observed video frame and existing normal frames. The proposed method is evaluated and validated on several video surveillance datasets.
doi_str_mv 10.1016/j.ijleo.2017.07.064
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subjects Abnormal event detection
Engineering Sciences
Hidden Markov model
Optical flow
Signal and Image processing
title Abnormal event detection based on analysis of movement information of video sequence
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