A method for tracking an object, the method comprising: extracting conspicuous portions of a target object detected from a disparity map of a current frame, wherein extracting the conspicuous portions of the target object detected from the disparity map of the current frame includes performing clustering for disparity points of the target object detected from the disparity map of the current frame, and taking clusters obtained by the clustering as the conspicuous portions; performing clustering for disparity points in a disparity map of a next frame to form a plurality of clusters (S1-S6); calculating, for each conspicuous portion of the target object, similarity between each cluster of said plurality of clusters and the conspicuous portion to determine candidate clusters (A-D) similar to the conspicuous portion; classifying, based on positional relation among the conspicuous portions of the target object, a plurality of the candidate clusters (A-D) that belong to a same object into the same group, resulting in a plurality of groups of clusters, wherein if positional relation among n candidate clusters, which are similar to n different conspicuous portions, respectively, is consistent with the positional relation among the n different conspicuous portions, the n candidate clusters belong to the same object, where 1<n≤M, and M is the number of the conspicuous portions; determining, for each group, based on the similarity between each candidate cluster included in the group and the corresponding conspicuous portion, similarity between the group and the target object; and selecting the group with the highest similarity and taking a position of the selected group as a position of the target object in the disparity map of the next frame. extracting conspicuous portions of a target object detected from a disparity map of a current frame, wherein extracting the conspicuous portions of the target object detected from the disparity map of the current frame includes performing clustering for disparity points of the target object detected from the disparity map of the current frame, and taking clusters obtained by the clustering as the conspicuous portions; performing clustering for disparity points in a disparity map of a next frame to form a plurality of clusters (S1-S6); calculating, for each conspicuous portion of the target object, similarity between each cluster of said plurality of clusters and the conspicuous portion to determine candidate clusters (A-D) similar to the conspicuous portion; classifying, based on positional relation among the conspicuous portions of the target object, a plurality of the candidate clusters (A-D) that belong to a same object into the same group, resulting in a plurality of groups of clusters, wherein if positional relation among n candidate clusters, which are similar to n different conspicuous portions, respectively, is consistent with the positional relation among the n different conspicuous portions, the n candidate clusters belong to the same object, where 1<n≤M, and M is the number of the conspicuous portions; determining, for each group, based on the similarity between each candidate cluster included in the group and the corresponding conspicuous portion, similarity between the group and the target object; and selecting the group with the highest similarity and taking a position of the selected group as a position of the target object in the disparity map of the next frame.