Title :
Video-Based Abnormal Human Behavior Recognition—A Review
Author :
Popoola, Oluwatoyin P. ; Wang, Kejun
Author_Institution :
Pattern Recognition & Intell. Syst. Lab., Harbin Eng. Univ., Harbin, China
Abstract :
Modeling human behaviors and activity patterns for recognition or detection of special event has attracted significant research interest in recent years. Diverse methods that are abound for building intelligent vision systems aimed at scene understanding and making correct semantic inference from the observed dynamics of moving targets. Most applications are in surveillance, video content retrieval, and human-computer interfaces. This paper presents not only an update extending previous related surveys, but also a focus on contextual abnormal human behavior detection especially in video surveillance applications. The main purpose of this survey is to extensively identify existing methods and characterize the literature in a manner that brings key challenges to attention.
Keywords :
content-based retrieval; human computer interaction; inference mechanisms; pattern recognition; video retrieval; video surveillance; activity patterns; contextual abnormal human behavior detection; human-computer interfaces; intelligent vision systems; moving targets; scene understanding; semantic inference; video content retrieval; video surveillance applications; video-based abnormal human behavior recognition; Behavioral science; Feature extraction; Hidden Markov models; Human factors; Surveillance; Tracking; Anomaly detection; behavior modeling; human action recognition; video surveillance;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/TSMCC.2011.2178594