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학술대회 Adult Image Detection with Close-Up Face Classification
Cited 4 time in scopus Download 2 time Share share facebook twitter linkedin kakaostory
최병철, 김정녀, 류재철
International Conference on Consumer Electronics (ICCE) 2009, pp.1-2
08MS1300, 저비용 대규모 글로벌 인터넷 서비스 솔루션 개발, 남궁한
The SVM (support vector machine) and the SCM (skin color model) are used for detection of adult contents. The SVM consists of multi-class learning model and is very effective method for face detection, but complex. On the contrary, the SCM is very simple for detecting the adult images using skin ratio derived from statistical characteristics of RGB color information, but less effective in close-up facial images. So, we propose a hybrid scheme that combines the SVM for the 1st filtering scheme using 3-class learning model (with classes of objectionable, non-objectionable and close-up facial image) with the SCM for the 2nd filtering scheme using skin ratio. The performance of proposed scheme improves about 2.5% ~ 4.6% in the true positive rate and about 4.6% in the false positive rate. © 2009 IEEE.
KSP 제안 키워드
Color information, Face detection, Facial image, False Positive Rate, Hybrid Scheme, Learning model, RGB color, Statistical characteristics, Support VectorMachine(SVM), True positive rate, adult image detection