Abnormal behavior recognition for intelligent video surveillance systems: A review

被引：234

作者：

Ben Mabrouk, Amira ^{[1
]}

Zagrouba, Ezzeddine ^{[1
]}

机构：

[1] Univ Tunis El Manar, Higher Inst Comp, Res Team Intelligent Syst Imaging & Artificial Vi, Lab LIMTIC, Aryanah 2036, Tunisia

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2018年 / 91卷

关键词：

Computer vision; Video surveillance system; Behavior representation; Behavior modeling; ANOMALY DETECTION; EVENT DETECTION; FALL DETECTION; TRACKING; LOCALIZATION; OPTIMIZATION; MODEL;

D O I：

10.1016/j.eswa.2017.09.029

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the increasing number of surveillance cameras in both indoor and outdoor locations, there is a grown demand for an intelligent system that detects abnormal events. Although human action recognition is a highly reached topic in computer vision, abnormal behavior detection is lately attracting more research attention. Indeed, several systems are proposed in order to ensure human safety. In this paper, we are interested in the study of the two main steps composing a video surveillance system which are the behavior representation and the behavior modeling. Techniques related to feature extraction and description for behavior representation are reviewed. Classification methods and frameworks for behavior modeling are also provided. Moreover, available datasets and metrics for performance evaluation are presented. Finally, examples of existing video surveillance systems used in real world are described. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：480 / 491

页数：12

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