Object tracking using improved Camshift with SURF method

Abstract

Camshift is an effective algorithm for real time dynamic target tracking applications, which only uses color features and is sensitive to illumination and some other environment factors. When similar color existing in the background, traditional Camshift algorithm may fail, that is the target getting lost. To solve the problem, an improved Camshift algorithm is firstly proposed in this paper to reduce the influence of illumination interference. Besides, a method judging whether the target is lost is also proposed. Once the target is judged lost, the Speeded Up Robust Features (SURF) is utilized to find it again and the improved Camshift keeps on tracking the target continuously. SURF is invariant to scale, rotation and translation of images. We program in C++ based on OpenCV. The results prove that the proposed method is more robust than the traditional Camshift and give better tracking performance than some other improved methods.