Before revision:  and 2) non-parametric Bayesian priors over segmentation maps (ie partitions of the visual space). We provide an algorithm for learning and inference , validate it on synthetic data , and illustrate how the two components of our model improve segmentation of natural images .
After revision:  and 2) the preference of humans to form contiguous partitions of visual space. We develop an efficient algorithm for training and inference based on expectation-maximization and validate it on synthetic data , and illustrate how the two components of our model improve segmentation of natural images .