Abstract:

In order to solve the singular describing of candidate target in object tracking, an algorithm based on adaptive feature fusion of visual significant feature is proposed. The quaternion model of target composed of intensity, motion, color and the change of color feature is built, and the PQFT (Phase spectrum of Quaternion Fourier Transform) is used to extract saliency map. According to similarity coefficient, the fusion weights are adaptively adjusted and the color feature is combined to ensure accurate tracking. The experimental results demonstrate that the approach can effectively overcome the part occlusion and the interference of background, realizing the accurate tracking under the case of complex background.

Key words: object tracking, saliency map, visual significant feature, feature fusion