Dense disparity estimation using a hierarchical matching technique from uncalibrated stereo vision

In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, the proposed disparity estimation algorithm performs a 2-D correspondence search using a hierarchical search pattern. The disparity value is then defined using the distance of the matching position. Therefore, the proposed algorithm can process non-rectified stereo image pairs, maintaining the computational load within reasonable levels.