Multiple human tracking based on daubechies complex wavelet transform combined with histogram of templates features

In video processing, tracking objects that are in motion has attracted lot of interest of the researchers all over the world. In numerous computer vision applications, such as monitoring traffic, remote video surveillance automation, human tracking, etc, moving object detection in video sequence is the major step of knowledge extraction. In this paper, an effective human tracking system based on Daubechies Complex Wavelet Transform (DaubCxWT) combined with histogram of template is introduced. This transform is suitable to track a person in video sequences because of its approximate shift-invariance nature. Initially, DaubCxWT co-efficients associated to the person are computed. Then, in Daubechies complex wavelet domain, the energy of these co-efficients is compared to the neighbouring object, to carry out tracking in the consecutive frames. Histogram of template feature is used to extract the texture and gradient information for the human detected. Daubechies Complex Wavelet co-efficients and histogram of template features are combined to form feature vector. In order to build feature vector for every pixel in that area, the calculated coefficients are utilised. Further, by making use of the generated feature vectors inside an adaptive search window, optimal search for the best match is performed. Search window adaption is employed to estimate the speed and direction of the person, in motion. This method has shown appreciable results.