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Content Based Video Retrieval for Obscene Adult Content Detection

机译:基于内容的淫秽成人内容检测视频检索

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With the advancement in networking, content produced and distributed over the Internet is exponentially increasing. This imposes the threat of distribution of obscene content freely and largely, urging mechanisms to control access by minor aged users. Manual retrieval and indexing of material is impossible for large video repositories. This paper proposes a method to detect videos with obscene adult content using content based video retrieval techniques. We propose an algorithm to summarize the video by extracting keyframes that mark video shot boundaries and apply BoVW algorithm to classify keyframes indicating the presence of obscenity. Despite the ignorance of high-level features in temporal domain, a higher recognition rate of 85 % with spatial information alone is proved. Further, we show the irrelevance of color information to detect nudity in videos when using BoVW.
机译:随着网络的进步,在互联网上产生和分发的内容是指数增长的。这赋予淫秽内容的分配威胁自由,主要是,敦促机制通过轻微老年用户控制访问。对于大型视频存储库,无法手动检索和索引材料是不可能的。本文提出了一种使用基于内容的视频检索技术来检测淫秽成人内容的视频的方法。我们提出了一种算法来通过提取标记视频拍边界的关键帧来总结视频并应用BOVW算法来分类指示淫秽的存在的关键帧。尽管时间域中的高级特征无知,但仅证明了仅具有空间信息的较高识别率为85%。此外,我们展示了在使用BOVW时检测彩色信息中的裸露的无关。

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