Binocular Stereo Dense Matching in the Presence of Specular Reflections

Wei Zhou, Chandra Kambhamettu

Abstract: Traditional stereo correspondence algorithms rely heavily on the Lambertian model of diffuse reflectance. While this diffuse assumption is generally valid for much of an image, processing of regions that contain specular reflections can result in severe matching errors. In this paper, We address the problem of binocular stereo dense matching in the presence of specular reflections by introducing a novel correspondence measurement which is robust to the specular reflections. Combining our novel correspondence measurement with various local or global optimatization methods, accurate depth can be estimated for both diffuse and specular regions. Unlike the previous works which seek to eliminate or avoid specular reflections using image preprocessing or multibaseline stereo, our approach works in its presence. Our approach is general and fits well in various stereo frameworks. Experiments with both synthetic and real images demonstrate the effectiveness and robustness of our approach.