Research on Intelligent Video Surveillance techniques for suspicious activity detection critical review

Abstract

Surveillance denotes close observation and monitoring of behavior, activities, or other dynamic information, of people or objects for the purpose of influencing, managing, directing, or protecting them. With advancement in technology and emerging of various intelligent prediction techniques, it has now become possible to imbibe the traditional video surveillance with intelligence to identify or take decision according to the scenarios. Intelligent video surveillance system (IVS) based on image recognition is widely employed to effectively avert crimes and provide public security. Due to the high complexity of processing real time data and analysis/understanding of image contents, a well-developed user friendly and cost effective product is not present for use. This paper is an outcome of comparative analysis of extracts drawn from literature review of 57 IEEE papers ranging from year 1977 to the year 2015, carried out to understand the suspicious activity detection methodologies used for detecting abnormal human behavior, tracing abandoned object, or unattended baggage etc., which led to an extensive comparison between various proposed methods. Many technologies, mostly based on intelligent techniques like Neural Systems, Fuzzy Logic, Support Vector Machine, Genetic Algorithm etc. emerged out as basis for intelligence in such systems. The outcome of the review is presented in form of various findings, which includes techniques and methods used to solve particular research problem, along with their strengths and weaknesses and the scope for the future work in the area.