Cross Validation and Segment Support for Stereo Belief Propagati

Typically, algorithms for generating stereo disparity maps have been developed to minimise the energy equation of a single image. This paper proposes a method for implementing cross validation in a belief propagation optimisation. When tested using the Middlebury online stereo evaluation, the cross validation improves upon the results of standard belief propagation. Furthermore, it has been shown that regions of homogeneous colour within the images can be used for enforcing the so-called "segment constraint". Developing from this, segment support is introduced to boost belief between pixels of the same image region and improve propagation into textureless regions