Robust adaptive window matching by homogeneity constraint and integration of descriptions

The crucial element of existing binocular stereo algorithms is to establish point to point correspondences in the two images. In order to overcome the problem of distortions, a promising approach is to locally adapt the correlation window size. In this paper we derive two major simplifications of an existing adaptive window approach. These simplifications are justified for images of objects with constant reflection properties. For this purpose the homogeneity constraint is introduced. In order to increase the robustness of the simplified algorithm the integration with a local description matching approach is proposed. The new algorithm is extended by subpixel approximation. Experiments are performed on real data and compared with manual measurements. A numerical analysis of the results demonstrates the achieved accuracy anal robustness.