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Trajectory clustering in crowded video scenes is very challenging. In this paper, we propose to use a belief based correlated topic model (BCTM) to learn discriminative middle level features for trajectory clustering. By constructing a scene prior based joint Gaussian distribution, the BCTM can uncover relations between trajectory clusters and the middle level features using a parameter estimation...
Pedestrian detection problem has been a touchstone of various image feature descriptors. In this paper, we evaluate four kinds of representative local descriptors (HOG, Haar-like, SURF and LBP) for pedestrian representation. Our goal is to find out the best combination of feature descriptors by analyzing and evaluating the complementarities of them. With the cross validation method, we first find...
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO) features are proposed as the feature representation. The features are extracted on square image blocks of various sizes (called units), containing coarse and fine features in which coarse ones are the unit orientations...
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