Abnormal behavior recognition for intelligent video surveillance systems: A review

- Different levels of an intelligent video surveillance system (IVVS) are studied in this review.
- Existing approaches for abnormal behavior recognition relative to each level of an IVVS are extensively reviewed.
- Challenging datasets for IVVS evaluation are presented.
- Limitations of the abnormal behavior recognition area are discussed.

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.