计算机工程与应用Issue(19)：173-177,5.DOI:10.3778/j.issn.1002-8331.1211-0130
基于优化加权参数的AdaBoost人脸检测算法
AdaBoost face detection algorithm based on optimized weighting parameter
缪丹权 1郑河荣 1顾国民1
作者信息
- 1. 浙江工业大学 计算机科学与技术学院，杭州 310023
- 折叠
摘要
Abstract
Existed single threshold methods will cause highly false recognition rates in face detection. This paper proposes a fast AdaBoost algorithm based on optimized weighting parameter. Firstly, algorithm changes the solving formula of weighted parameter to get low false alarm rates even under the premise of low false recognition rates. Secondly, dual-threshold is obtained by calculating the feature-value curve. Finally, the detected dual thresholds are used to form weak classifiers, which can form an ensemble classifier. Experimental results show that it not only improves the accuracy of detection, but also ameliorates the training and detecting time since dual-threshold can decrease the times of searching.关键词
人脸检测/Haar-like特征/AdaBoost算法/双阈值/优化加权参数Key words
face detection/Haar-like feature/AdaBoost algorithm/dual-threshold/optimized weighting parameter分类
信息技术与安全科学引用本文复制引用
缪丹权,郑河荣,顾国民..基于优化加权参数的AdaBoost人脸检测算法[J].计算机工程与应用,2014,(19):173-177,5.
