Abstract

An accurate stereo matching method developed by exploiting the two techniques, discrete-coded structured-light projection and image-guided cost volume filtering, is proposed. The former increases the distinctiveness of pixels by projecting a discrete pattern to the scene, and the latter helps to recover accurate object boundaries. In addition, a previous fast cost volume filtering approach is extended to better preserve slanted surfaces, and a suitable post-processing algorithmis also suggested for the proposed method. The performance of the proposed method is experimentally verified by comparing the results with those of other algorithms qualitatively and quantitatively in an indoor environment.