Paper Title:
Performance Improvement on Edge-Based Human Detection Using Local Contrast Enhancement
  Abstract

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)
Chapter
Chapter 1: Computer-Aided Manufacturing
Edited by
Wu Fan
Pages
615-620
DOI
10.4028/www.scientific.net/AMR.383-390.615
Citation
X. Yuan, X. Y. Wei, Y. D. Song, "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
$32.00
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