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학술대회 Obscene Video Detection by Multiple-Classifier Fusion
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최진우, 한승완
International Conference on Advanced Communication Technology (ICACT) 2015, pp.1-4
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.
KSP 제안 키워드
Detection Method, Global histogram, Multiple classifier fusion, Precision and recall, Real-world, Skin Region Analysis, Video contents, Video detection, fusion method, image detection, recall-oriented