Markov random fields for vision and image processing edited by andrew blake pushmeet kohli and carsten rother state of the art research on mrfs successful mrf applications and advanced topics for future study. Markov random fields for vision and image processing edited by andrew blake pushmeet kohli and carsten rother the mit press cambridge massachusetts london england contents 1 introduction to markov random fields 1 andrew blake and pushmeet kohli 1 algorithms for inference of map estimates for mrfs 29 2 basic graph cut algorithms 31 yuri boykov and vladimir kolmogorov 3 optimizing . Markov random fields mrfs are a popular graphical model for reconstruction and recognition problems in computer vision and robotics including 2d and 3d semantic segmentation stereo. This post covers markov random fields and their application to specific problems in image processing we dont go deep or formal just intuitive we dont go deep or formal just intuitive a markov random field is a graph whose nodes model random variables and whose edges model desired local influences among pairs of them