Abstract:

In this paper, we proposed a method for identifying and tracking moving objects in binocular vision based on disparity computing and ScaleInvariant Feature Transform (SIFT) . Firstly, we employ the gradientbased stereo matching algorithm to construct the disparity mapping between the left and the right views. Based on SIFT feature matching, the disparity mapping is applied to improve the object matching accuracy in binocular vision. The disparity mapping and regional growth are used to track moving objects in the left and right views respectively. Experimental results show that of the proposal has higher accuracy and can track the same object in the left and right views of a video.

Key words: disparity stereo matching;scale-invariant feature transform(SIFT);target recognition;object tracking;regional growth