• Title/Summary/Keyword: Injurious Moving Picture

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A Realization of Injurious moving picture filtering system with Gaussian Mixture Model and Frame-level Likelihood Estimation (Gaussian Mixture Model과 프레임 단위 유사도 추정을 이용한 유해동영상 필터링 시스템 구현)

  • Kim, Min-Joung;Jeong, Jong-Hyeog
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.2
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    • pp.184-189
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    • 2013
  • In this paper, we propose the injurious moving picture filtering system using certain sounds contained in the injurious moving picture to filter injurious moving picture which is distributed without limitation in internet and internet storage space. For this purpose, the Gaussian Mixture Model which can well represent the characteristics of the sound, is used and frame level likelihood estimation is used to calculate the likelihood between filtering target data and the sound models. Also, the pruning method which can real-time proceed by reducing the comparing number of data, is applied for real-time processing, and MWMR method which showed good performance from existing speaker identification, is applied for the distinguish performance of high precision. In the identification experiment result, in case of the frame rate which is the proportion of total frame to high likelihood frame, is set to 50%, identification error rate is 6.06%, and in case of frame rate is set to 60%, error rate is 3.03%. As the result, the proposed system can distinguish between general and injurious moving picture effectively.