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A novel approach is presented to locate dense crowd of people in a network of fixed cameras given the severely degraded background subtracted silhouettes. The problem is formulated as a sparsity constrained inverse problem using an adaptive dictionary constructed on- line. The framework has no constraint on the number of cameras neither on the surface to be monitored. Even with a single camera, partially occluded and grouped people are correctly detected and segmented. Qualitative results are presented in indoor and outdoor scenes.
Mohamed Farhat, Davide Bernardo Preso, Armand Baptiste Sieber
Pascal Fua, Pavan P Ramdya, Adám Gosztolai, Victor Lobato Rios, Helge Jochen Rhodin, Semih Günel, Daniel Eduardo Morales Garza, Marco Pietro Abrate
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