An intelligent vehicle tracking technology based on SURF feature and Mean-shift algorithm

In traffic video surveillance system, target-level tracking and feature-level tracking are two important areas for research. Therefore, the combination between them is an interesting question. Mean-shift is a traditional target-level tracking algorithm with no adaptation to vehicle scale and orientation change. In order to solve the problem, algorithm combine SURF (speed-up robust feature) feature with Mean-shift algorithm is proposed in this article. Feature point scale and orientation information is used to make algorithm with scale and orientation adaptability. The tracking model of the vehicle is also updated in the algorithm. Experimental results show that the proposed algorithm provides better tracking result than traditional algorithm of vehicle scale and orientation change. Furthermore, the tracking result is also more accurate.