A stereo matching algorithm based on shape similarity for indoor environment model building

A novel stereo matching algorithm has been proposed in this paper based on the observation that there are plenty of horizontal features in indoor environments. In this algorithm, the shape identity of all horizontal feature correspondences is achieved by means of a special image transformation-reprojection transformation. By using edge string as an intermediate structure, a generalized Hough transformation strategy fuses a variety of criteria, such as shape similarity disparity continuity and pixel attribution similarity, etc., together. In this way it copes with the correspondence of horizontal and non-horizontal features for 3D environment model building. First the principle of reprojection transformation using calibrated or uncalibrated images are discussed, then the generalized Hough transform strategy is addressed. Preliminary experimental results indicate that the algorithm is an effective and efficient method for indoor environment model building by using stereo methodology