Temporal consistent stereo matching approach for road applications

In this paper, we present a fast approach for matching stereo images acquired by a stereo sensor embedded in a moving vehicle. The proposed approach exploits the disparity map already computed at the preceding frame to improve the matching results at the current one. An edge association method is used to track the edge curves over time. Local disparity constraints are computed for all the edge points that belong to the tracked edge curves. For the rest of edge points, we use a global disparity constraint, which is computed for each image line based on the preceding v-disparity. We integrate these constraints in the dynamic programming algorithm, which increases the matching results and speeds up the matching process.