Over in Fergus's computer science group, Deqing Sun (Brown) gave a very nice talk about measuring motion in image sequences (think movies) by building a generative model of moving layers with sharp boundaries. He constructs a prior over image segmentations by segmenting the image using threshold-crossing of a (very local) smooth Gaussian process; this permits an analytic prior. The results are beautiful and effective and conform to common sense and also come close to world-record performance against quantitative benchmark tests (with known ground truth). His system performs well in part because it is a (approximate, simplified, sensible) full generative model for the data: It has a large number of parameters, a proper prior over those parameters, and a sensible likelihood function, and he can optimize it. He didn't try to sample from the posterior PDF, but he has only worked (so far) at very high signal-to-noise.
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