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- Issue Date
- 2014-10
- Citation
- 대한임베디드공학회논문지, v.9, no.5, pp.261-268
- ISSN
- 1975-5066
- Publisher
- 대한임베디드공학회
- Language
- Korean
- Type
- Journal Article
- Abstract
- 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 Keywords
- AdaBoost Algorithm, Application System, Classification rate, Classifier Combination, Detection Method, Face image processing, Facial expression recognition(FER), False Positive(FP), False Positive Rate, Gender Identification, Haar-like