Title :
Pedestrian Detection Based on ISC in Infrared Images
Author :
Chen, Lianna ; Li, Wenshu ; Xu, Zhengxi ; Tang, Limei
Abstract :
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.
Keywords :
Context; Educational institutions; Feature extraction; Filtering; Histograms; Image edge detection; Shape; Bilateral Filtering; Infrared images; Pedestrian Detection; Shape Context;
Conference_Titel :
Networking and Distributed Computing (ICNDC), 2012 Third International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4673-2858-6
DOI :
10.1109/ICNDC.2012.47