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저자
임길택, 강현우, 한병길, 이종택
발행일
201410
출처
대한임베디드공학회논문지, v.9 no.5, pp.261-268
ISSN
1975-5066
출판사
대한임베디드공학회
DOI
https://dx.doi.org/10.14372/IEMEK.2014.9.5.261
협약과제
14ZI2200, 대경권 지역전략산업 기반 융합기술 지원사업, 정윤수
초록
Face detection is essential to the full automation of face image processing application system such as face recognition, facial expression recognition, age estimation and gender identification. It is found that local image features which includes Haar-like, LBP, and MCT and the Adaboost algorithm for classifier combination are very effective for real time face detection. In this paper, we present a face detection method using local pixel direction code(PDC) feature and lookup table classifiers. The proposed PDC feature is much more effective to dectect the faces than the existing local binary structural features such as MCT and LBP. We found that our method’s classification rate as well as detection rate under equal false positive rate are higher than conventional one.
KSP 제안 키워드
AdaBoost Algorithm, Application System, Classification rate, Classifier Combination, Detection Method, Face detection, Face image processing, Facial Expression Recognition(FER), False Positive Rate, Gender identification, Haar-like