In this paper we present a comparative critical study of visual and non-visual sensors used in crowd behavior analysis. The understanding of crowd has main impact of the analysis how much they support the system is the key factor of the analysis. The surveillance and security prospects are the main feature for crowd that can make system easy and gives better result. The visual sensors that have been widely used are wireless sensor network, computer vision, smart camera, sensor fusion and few more; and the non-visual sensors are regarding the call, IEEE 802, 11 signals measurement, Smart Evactrack, Social Network and Bluetooth etc. This comparative study identified the different analysis of crowd behavior and after analysis we show which technique is better to another one. The smart devices are used now days for surveillance and gives better result in crowd behavior analysis.
Target detection is an approach to extract object from image, however it is difficult task when object is moving. Moving target detection is a key area in image processing such as traffic control system, activity monitoring security system, CCTV footage etc. For detecting a moving object in dynamic background, a background subtraction based method has already been suggested. These methods does not give better results when object is moving very fast, object is very tiny and presence of lighting effect. To overcome these problems, we propose a new method for Moving Target Detection in Dynamic Background. It achieves dynamic scene using certain probability of time and subsequent frame difference method and addresses the difficult scenario, where object is moving very fast and background changes frequently. In order to increase the accuracy of a proposed method, rate of change in background is calculated in fixed time of interval which will maintain dynamic behavior of object as well as background. The experimental results show that the proposed method can detect moving object more efficiently and completely in both cases online as well as offline video
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