Pedestrian Attribute Recognition with Occlusion in Low Resolution Surveillance Scenarios

In surveillance scenarios, the pedestrian images are often facing poor resolution problems or the images are often suffered the occlusion problems. These problems make pedestrian attribute recognition more difficult. In order to solve this problem, we propose an improved pedestrian attribute recognition method based on hand-crafted feature. In this method, we use Patch Match algorithm as pedestrian image preprocessing to enhance the pedestrian images. Experiments show that this method proposed performs excellent when the pedestrian images suffer occlusion problem and the method is robust to low resolution problem.

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