文章基本信息

标题：Abnormal Human Behavior Detection in Videos: A Review
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作者：Huiyu Mu ; Ruizhi Sun ; Gang Yuan 等
期刊名称：Engineering Economics
印刷版ISSN：2029-5839
出版年度：2021
卷号：50
期号：3
DOI：10.5755/j01.itc.50.3.27864
语种：English
出版社：Kaunas University of Technology
摘要：Modeling human behavior patterns for detecting the abnormal event has become an important domain in recentyears. A lot of efforts have been made for building smart video surveillance systems with the purpose ofscene analysis and making correct semantic inference from the video moving target. Current approaches havetransferred from rule-based to statistical-based methods with the need of efficient recognition of high-levelactivities. This paper presented not only an update expanding previous related researches, but also a study coveredthe behavior representation and the event modeling. Especially, we provided a new perspective for eventmodeling which divided the methods into the following subcategories: modeling normal event, predictionmodel, query model and deep hybrid model. Finally, we exhibited the available datasets and popular evaluationschemes used for abnormal behavior detection in intelligent video surveillance. More researches will promotethe development of abnormal human behavior detection, e.g. deep generative network, weakly-supervised. It isobviously encouraged and dictated by applications of supervising and monitoring in private and public space.The main purpose of this paper is to widely recognize recent available methods and represent the literature ina way of that brings key challenges into notice.
关键词：abnormal detection;video surveillance;behavior representation;event modeling