Implementation of the DMV-based stereo object tracking system

Abstract

In this paper, a new stereo object tracking system using the disparity motion vector(DMV) is proposed. Here, the DMV is defined as a disparity difference between two time-sequential disparity maps of T-1 and T frames and it can be sequentially estimated from the disparity maps which are extracted from the input stereo sequence. Here, the disparity maps are obtained by using the feature-based matching algorithm, in which the block size and the search range for the feature-based matching are given by N x × N y = 1 × 1 and S x = ±32, respectively. And then, the DMV can be estimated by calculating the motion difference between two consecutive disparity maps. Basically, the DMV has a relatively large change of disparity values in the target region because of the target's movement, whereas it has very low difference values in the background region; there are almost no changes by comparing with the target region. As a result, the DMV can provide us with the motional information of a moving target by showing a large disparity difference in the target area. That is, the dynamic relationship between these disparity vectors of T-1 and T frames seems to be very similar to that between the motion vectors of T-1 and T frames in the sequence of the conventional 2D video images. Accordingly, the target area and its location coordinates can be detected by using these DMV maps. Basing on these locational data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and as a result, real-time stereo tracking of a moving target can be achieved. From some experiments with 9 frames of the stereo sequence having 256×256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.02 % on average. This good experimental result finally suggests a possibility of implementing the DMV-based stereo object tracking system.