A novel approach based on 2D - DWT and variance method for human detection and tracking in video surveillance applications

Moving object detection is very important in modern world for fast video surveillance. There are various methods used for detecting moving objects out of which frame differencing method is widely used and is most efficient method. In this paper we focus on the surveillance at the most secured areas such as airports, defense establishments, power stations etc. Similarly, the area where no human is allowed without authority to enter such as bank locker rooms, restricted military area etc. automotive surveillance and traffic monitoring plays a vital role. In real time surveillance system, storing the captured video and detecting object are two most important issues. Storing such videos needs more memory and the detection of the object is also need to be fast. To solve these problems compression and fast object detection is required. To detect the moving object, detection of its edges and location in the frame are important steps. In this paper we propose a mechanism to use discrete wavelet transform (DWT) for two purposes for compression and edge detection, whereas to locate the object we propose variance method on to the 2-D DWT outputs of video frames. For this analysis HAAR wavelet is used as reference.