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Detection of Abnormal Behavior by Scene Analysis in Surveillance Video
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 Title & Authors
Detection of Abnormal Behavior by Scene Analysis in Surveillance Video
Bae, Gun-Tae; Uh, Young-Jung; Kwak, Soo-Yeong; Byun, Hye-Ran;
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In intelligent surveillance system, various methods for detecting abnormal behavior were proposed recently. However, most researches are not robust enough to be utilized for actual reality which often has occlusions because of assumption the researches have that individual objects can be tracked. This paper presents a novel method to detect abnormal behavior by analysing major motion of the scene for complex environment in which object tracking cannot work. First, we generate Visual Word and Visual Document from motion information extracted from input video and process them through LDA(Latent Dirichlet Allocation) algorithm which is one of document analysis technique to obtain major motion information(location, magnitude, direction, distribution) of the scene. Using acquired information, we compare similarity between motion appeared in input video and analysed major motion in order to detect motions which does not match to major motions as abnormal behavior.
Abnormal behavior;Scene analysis;Intelligent surveillance System;
 Cited by
감시 영상에서 군중의 탈출 행동 검출,박준욱;곽수영;

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