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We enable highly improved performance of deformable model (snake) segmentation of a known type of object (human bladder) with unclear edges in a cluttered domain (abdominal CT scans). This is accomplished by learning an objective function from ground-truth contours in test images , using a nonparametric estimator of the distributions of chosen image(More)
We propose visual memes, or frequently reposted short video segments, for tracking large-scale video remix in social media. Visual memes are extracted by novel and highly scalable detection algorithms that we develop, with over 96% precision and 80% recall. We monitor real-world events on YouTube, and we model interactions using a graph model over memes,(More)