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We present a method for real-time simultaneous object recognition and segmentation based on cascaded discriminative Markov random fields. A Markov random field models coupling between the labels of adjacent image regions. The MRF affinities are learned as linear functions of image features in a structured max-margin framework that admits a solution via convex optimization. In contrast to other known...
We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to synthesize new trajectories. Our approach models physical trajectories as least-time trajectories realized by free particles moving along the geodesics of a curved manifold, reminiscent of the way light rays obey Fermat's principle...
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