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학술지 Disguised-Face Discriminator for Embedded Systems
Cited 12 time in scopus Download 2 time Share share facebook twitter linkedin kakaostory
저자
윤우한, 김도형, 윤호섭, 이재연
발행일
201010
출처
ETRI Journal, v.32 no.5, pp.761-765
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.10.1510.0139
협약과제
09IC1800, u-로봇 HRI 솔루션 및 핵심 소자 기술 개발, 황대환
초록
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. © 2010 ETRI.
키워드
AdaBoost, Discriminator, Disguised face
KSP 제안 키워드
AdaBoost learning algorithm, Embedded system, adaptive boosting(AdaBoost), look-up table