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학술대회 Obscene Video Detection by Multiple-Classifier Fusion
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저자
최진우, 한승완
발행일
201501
출처
International Conference on Advanced Communication Technology (ICACT) 2015, pp.1-4
DOI
https://dx.doi.org/10.1109/FCV.2015.7103753
협약과제
14MS2700, 스마트 단말용 스트리밍 유해 컨텐츠 차단 기술 개발, 한승완
초록
Obscene video detection is a core technology to prevent inappropriate access of children or teenagers to obscene video contents. There are many obscene video or image detection methods such as skin region analysis based methods, global histogram based methods. However, accuracy of these methods are not high enough to be deployed in the real-world environment. In this paper, we propose an obscene video detection method by multiple-classifier fusion. Three fusion methods are proposed: precision-oriented, recall-oriented, and accuracy-oriented. Experimental results show that by using the multiple classifier fusion method, superior accuracy, precision and recall can be achieved while exploiting the complementary behavior of different obscene classifiers.
키워드
Classifier-Fusion, Image Classification, Obscene Video Detection, Video Classification
KSP 제안 키워드
Detection Method, Global histogram, Image classification, Multiple classifier fusion, Precision and recall, Real-world, Skin Region Analysis, Video classification, Video contents, Video detection, fusion method