1. An object tracking method comprising: an obtention step of obtaining a grayscale image sequence and its corresponding depth image sequence; a prediction step of predicting a candidate target region of a tracking object in at least one of a current grayscale image and it corresponding depth image; a determination step of determining a depth weight image of the candidate target region, wherein, the depth weight image includes depth weight information of each pixel, and the depth weight information of each pixel refers to depth information based on this pixel and a probability of this pixel belonging to the tracking object; an acquirement step of acquiring a target template, wherein, the target template is expressed by a probability density distribution of features; an expression step of expressing, by a probability density distribution of features, a candidate target whose position moves in the candidate target region, wherein, in a process of estimating probability densities of features of the candidate target, each pixel is weighted based on both color space information and the depth weight information of this pixel; a calculation step of calculating, based on a probability density expression of the target template and a probability density expression of the candidate target, a similarity between the target template and the candidate target, so as to get a confidence level image of the candidate target region; and a location step of locating, based on the confidence level image of the candidate target region, a position of the tracking object in the corresponding current image.