Daubechies Complex Wavelet Transform Based Moving Object Tracking

This paper describes a new method for moving object tracking, using complex wavelet transform. Real-valued wavelet transform is widely used in tracking applications, but it suffers from shift-sensitivity. Daubechies complex wavelet transform is more suitable for tracking due to approximate shift-invariance nature. The proposed method is intelligent enough to segment the object from a scene. Segmentation in the first frame has been done by computing multiscale correlation of imaginary component of complex wavelet coefficients and then object is tracked in next frames by computing the energy of complex wavelet coefficients corresponding to the object area and matching this energy to that of the neighborhood area. The proposed method is simple and does not require any other parameter except complex wavelet coefficients for segmentation as well as tracking