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We present a unified method for simultaneously acquiring both the location and the silhouette shape of people in outdoor scenes. The proposed algorithm integrates top-down and bottom-up processes in a balanced manner, employing both appearance and motion cues at different perceptual levels. Without requiring manually segmented training data, the algorithm employs a simple top-down procedure to capture...
We present a method for the simultaneous detection and segmentation of people from static images. The proposed technique requires no manual segmentation during training, and exploits top-down and bottom-up processing within a single framework for both object localization and 2D shape estimation. First, the coarse shape of the object is learned from a simple training phase utilizing low-level edge...
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