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Content Based Video Retrieval for Obscene Adult Content Detection

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9492))

Abstract

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.

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Notes

  1. 1.

    \(H_1\) and \(H_2\) refer to normalized histograms of two frames.

  2. 2.

    TP- True Positive, TN- True Negative, FP- False Positive, FN- False Negative.

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Correspondence to Hasini Yatawatte .

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Yatawatte, H., Dharmaratne, A. (2015). Content Based Video Retrieval for Obscene Adult Content Detection. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_46

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  • DOI: https://doi.org/10.1007/978-3-319-26561-2_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26560-5

  • Online ISBN: 978-3-319-26561-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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