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This work describes a stereo algorithm that takes advantage of image segmentation, assuming that disparity varies smoothly inside a segment of homogeneous colour and depth discontinuities coincide with segment borders. Image segmentation allows our method to generate correct disparity estimates in large untextured regions and precisely localize depth boundaries. The disparity inside a segment is represented by a planar equation. To derive the plane model, an initial disparity map is generated. We use a window-based approach that exploits the results of segmentation. The size of the match window is chosen adaptively. A segment's planar model is then derived by robust least squared error fitting using the initial disparity map. In a layer extraction step, disparity segments that are found to be similar according to a plane dissimilarity measurement are combined to form a single robust layer. We apply a …