A novel approach toward pedestrian detection applied to infrared images using improved Shape Context feature (ISC) is proposed. We apply Bilateral Filtering for images to preserve the information of large sharp edges and to facilitate the task of Shape Context feature (SC) extracting. Then, we study an image descriptor based on an improved Shape Context feature (ISC), which is more robust to object deformation. For a test image, improved SC features are extracted and matched to the codebook. A voting scheme then obtains object locations from the matching results. Experimental results with Infrared Image Database demonstrate that our method is suitable for infrared images, and is promising.
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