Performance Improvement on Edge-Based Human Detection Using Local Contrast Enhancement

Abstract:

Article Preview

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.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

615-620

DOI:

10.4028/www.scientific.net/AMR.383-390.615

Citation:

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

Online since:

November 2011

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Price:

$35.00

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