Disguised-Face Discriminator for Embedded Systems

In this paper, we introduce an improved adaptive boosting (AdaBoost) classifier and its application, a disguised-face discriminator that discriminates between bare and disguised faces. The proposed classifier is based on an AdaBoost learning algorithm and regression technique. In the process, the lo...

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Bibliographic Details
Published inETRI journal Vol. 32; no. 5; pp. 761 - 765
Main Authors Yun, Woo-Han, Kim, Do-Hyung, Yoon, Ho-Sub, Lee, Jae-Yeon
Format Journal Article
LanguageKorean
Published 한국전자통신연구원 30.10.2010
ETRI
Subjects
AdaBoost
Disguised face
discriminator
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Summary:In this paper, we introduce an improved adaptive boosting (AdaBoost) classifier and its application, a disguised-face discriminator that discriminates between bare and disguised faces. The proposed classifier is based on an AdaBoost learning algorithm and regression technique. In the process, the lookup table of AdaBoost learning is utilized. The proposed method is verified on the captured images under several real environments. Experimental results and analysis show the proposed method has a higher and faster performance than other well-known methods.
Bibliography:KISTI1.1003/JNL.JAKO201071242949479
ISSN:1225-6463
2233-7326