Video target tracking method based on SURF (speeded-up robust features) feature point diagram matching and motion generating model

A video target tracking method based on an SURF (speeded-up robust features) feature point diagram matching and motion generating model belongs to the technical field of computer vision, which comprises the following steps: describing a target object using a partial feature point set; carrying out diagram matching on a feature point set obtained by detection in a new frame image and a target feature point set to obtain the motion information of a target partial feature point; portraying the relationship between the partial feature point motion and the target integral motion by using a generating model; calculating a target integral motion parameter by utilizing the maximum likelihood estimation in the partial feature point motion information; updating a mixing probability coefficient of the target feature point by utilizing an online expectation-maximization method; and judging through monitoring whether a background feature point enters a target area. The invention can be efficiently applicable to real tracking of a general target, and overcome the invalidation of the exisitng tracking method under the situations, such as illumination change, form change, complex background and target blocking and the like, and can track the video target efficiently, thereby giving correct, practical and valid motion information.