Abstract: The available feature-optical-flow algorithms have great shortages of computing complexity and anti-noise performance.Concerning this problem,a moving target tracking algorithm based on scale invariant feature transform and Kalman filter algorithm was proposed.First,the SIFT features are extracted in images.Then,the feature points of moving target are matched according to the minimum absolute error criterion and the optical flow vectors of SIFT features are estimated by Kalman filter algorithm.Finally,recognition and tracking of moving target are achieved using the clustering algorithm based on optical features.The experimental results suggest that the algorithm performs well on the feature points tracking in natural scene.The algorithm is easy to calculate and achieve .

Key words: Moving target tracking,Feature optical flow,Scale invariant feature transform,Kalman filter algorithm,Feature optical flow clustering