Automated video surveillance is an important research area in the commercial sector. Visual surveillance and monitoring of human activity requires people to be tracked as they move through a scene. Autonomous video surveillance and monitoring has a rich history. A new method for detecting and tracking multiple moving objects based on discrete wavelet transform and identifying the moving objects by their color and spatial information is proposed in this paper. Discrete wavelet transform can divide a frame into four different frequency bands without loss of the spatial information. Localization in both frequency and time/spatial domains is the greatest advantage of discrete wavelet transform over Fourier transform- based methods. The algorithm uses Background Subtraction and Boxed Based tracking for aforementioned goals. The proposed model has proved to be robust in different types of static background scenes. The Experimental results prove the feasibility of the proposed methods.