Stereo matching on objects with fractional boundary

Conventional stereo matching algorithms assume color constancy on the corresponding opaque pixels in the stereo images. However, when the foreground objects with fractional boundary are blended to the scene behind using unknown alpha values, due to the spatially varying disparities for different layers, the color constancy does not hold any more. In this paper, we address the fractional stereo matching problem. A probability framework is introduced to establish the correspondences of pixel colors, disparities, and alpha values in different layers. We propose an automatic optimization method to solve a Maximum a posteriori (MAP) problem using Expectation-Maximization (EM), given the input of only a narrow-band stereo image pair. Our method naturally encodes pixel occlusion in the formulation of layer blending without a special detection process. We demonstrate the effectiveness of our method using difficult stereo images.