Performance Improvement on Edge-Based Human Detection Using Local Contrast Enhancement
This paper presents a local contrast enhancement method, which is able to improve the detection performance of edge-based human detection. First, a neighborhood dependent local contrast enhancement method is used to enhance the images contrast. Next, the cascade AdaBoost classifier is used to discriminate between human and non-human. Experimental results show that the performance of our method is about 5% better than that of the conventional method.
X. Yuan et al., "Performance Improvement on Edge-Based Human Detection Using Local Contrast Enhancement", Advanced Materials Research, Vols. 383-390, pp. 615-620, 2012