Using an image tree to assist stereo matching

The method known as SSD, sum of squared difference, is a popular and moderately robust method for dense stereo matching, but it has several known limitations. Various refinements have been proposed, including actively changing the window shape during processing and multi-resolution analysis. We use the multi-scale tree representation of the image to generate window shapes that are well matched to image objects. We use the structure of the tree to refine our disparity search, creating a disparity tree. This tree is a close representation of the objects in the scene, and is a step towards creating a symbolic representation of objects within a scene. We find that the new method performs particularly well in regions of low texture: operating conditions that cause conventional methods to fail