Two-level searching tracking algorithm based on fast Fourier transform

In order to solve the problems of appearance change, scale and rotation change in the visual tracking, a two-level searching tracking algorithm based on Fast Fourier Transform(FFT)is proposed. It achieves two-level searching by establishing the object's kernel ridge regression model in the Cartesian coordinates and log-polar coordinates, respectively, and the efficiency can be improved by transforming the operation into the frequency domain based on FFT. First, the kernel ridge regression model is constructed in the Cartesian coordinate and the object's center position is obtained by the exhaustive search method based on the circular structure matrix. Then, it transforms the object area to the log-polar coordinates and searches the shift using the kernel ridge regression model in the log-polar coordinates. Finally, the object's state is calculated according to the searching results and the object's model is updated. Experimental results indicate that the proposed algorithm not only can obtain a distinct improvement in coping with the appearance change, scale and rotation change, but also have a high tracking efficiency.