测试科学与仪器2010，Vol.1Issue(2)：121-124,4.DOI:10.3969/j.issn.1674-8042.2010.02.05
Separated Same Rectangle Feature for Face Detection
Separated Same Rectangle Feature for Face Detection
摘要
Abstract
The paper proposes a new method of "Separated Same Rectangle Feature (SSRF)" for face detection.Generally,Haar-Like feature is used to make an Adaboost training algorithm with strong classifier.Haar-like feature is composed of two or more attached same rectangles,Inefficiency of the Haar-like feature often results from two or more attached same rectangles.But the proposed SSRF are composed of two separated same rectangles.So,it is very flexible and detailed.Therefore it creates more accuate strong classifier than Haar-Like feature.SSRF uses integral image to reduce executive time.Haar-Iike feature calculates the sum of intensities of pixels on two or more rectangles.But SSRF always calculates the sum of in-tensities of pixels on only two rectangles.The weak classifier of Ada-boost algorithm based on SSRF is faster than one based an Haar-likefeature.In the experiment,we use 1 000 face images and 1 000non-face images for Adaboost training.The proposed SSRF shows about 0,9% higher accuracy than Haar-Iike features.关键词
seperated same rectangle feature/Haar-like/discrete adaboost/featureKey words
seperated same rectangle feature/Haar-like/discrete adaboost/feature分类
天文与地球科学引用本文复制引用
Yong-hee HONG,Hwan-ik CHUNG,Hern-soo HAHN..Separated Same Rectangle Feature for Face Detection[J].测试科学与仪器,2010,1(2):121-124,4.基金项目
This work was Supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD),the MKE(The Ministry of Knowledge Economy,Korea),the ITRC(Information Technology Research Center) support program (NIPA-2009-(C1090-0902-0007)) （MOEHRD）
