Intelligent Video Surveillance Techniques for Human Fall Detection-Critical Review

“Surveillance is the monitoring of the behavior, activities, or other changing information, usually of people for the purpose of influencing, managing, directing, or protecting them”. This either includes observation from a distance by means of electronic equipment or interception of electronically transmitted information (like Internet traffic or phone calls). Surveillance systems have become increasingly popular in the globalization process. 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 dynamic scenario. Intelligent video surveillance system (IVS) based on image recognition is widely used to effectively prevent many crimes and helps to provide public security. Due to the high complexity in techniques such as real time processing and image contents analysis/understanding, a well-developed user friendly and cost effective product is not available until now in this field. This paper presents a critical review and comparative analysis of literature review of IEEE papers ranging from year 2008 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. However the focus of this paper is on methodologies used for detection of human fall and raise alarm for taking timely action. The outcome of this review is in the form of various findings, found under review process of this issue. The findings includes technologies and methodologies used to solve this particular research problem, along with their strengths and weaknesses and the scope for the future work in the area.