A cooperative integration of stereopsis and optic flow computation

A cooperative integration of stereopsis and optic flow computation is presented. Central to our approach is the modelling of the visual processes as a sequence of coupled Markov random fields by defining suitable interprocess interactions based on some natural constraints. The integration makes each of the individual processes better constrained and more reliable. Further, as a result of the integration, it becomes possible to accurately preserve the discontinuities in both the flow and the disparity fields along with the regions of stereo occlusion. Some results, both on noisy synthetic image data and real images are presented.