INTELLIGENT SURVEILLANCE BASED ON NORMALITY ANALYSIS TO DETECT ABNORMAL BEHAVIORS

被引:20
作者
Albusac, Javier [1 ]
Vallejo, David [1 ]
Jimenez-Linares, Luis [1 ]
Castro-Schez, J. J. [1 ]
Rodriguez-Benitez, Luis [1 ]
机构
[1] Univ Castilla La Mancha, Dept Informat Technol & Syst, Ciudad Real 13071, Spain
关键词
Behavior analysis; environment modeling; cognitive surveillance; INTRUSION DETECTION; RECOGNITION; MOTION; SYSTEM;
D O I
10.1142/S0218001409007612
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Intelligent surveillance refers to using Artificial Intelligence techniques in order to improve surveillance and deal with semantic information obtained from low-level security devices. In this context, the use of expert knowledge may offer a more realistic solution when dealing with the design of a surveillance system. In this work, a conceptual framework based on normality analysis to detect abnormal behaviors by means of normality concepts is presented. A normality concept specifies how a certain object should ideally behave in a concrete environment depending on such a concept. The definition of the normal path concept is studied in depth in order to analyze behaviors in an outdoor environment.
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页码:1223 / 1244
页数:22
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