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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
\(H_1\) and \(H_2\) refer to normalized histograms of two frames.
- 2.
TP- True Positive, TN- True Negative, FP- False Positive, FN- False Negative.
References
Children’s Internet Protection Act. https://en.wikipedia.org/wiki/Children%27s_Internet_Protection_Act/. Accessed 15 May 2013
Pornography Statistics. www.covenanteyes.com/. Accessed 15 May 2013
The Australian Communications and Media Authority. Online Regulation. http://www.acma.gov.au/theACMA/About/Corporate/Responsibilities/online-regulation-acma/. Accessed 15 May 2013
Behrad, A., Salehpour, M., Ghaderian, M., Saiedi, M., Barati, M.N.: Content-based obscene video recognition by combining 3D spatiotemporal and motion-based features. EURASIP J. Image Video Process. 2012(1), 1–17 (2012)
Ghodeswar, S., Meshram, B.B.: Content based video retrieval. In: Proceedings of ISCET, p. 135 (2010)
Kakumanu, P., Makrogiannis, S., Bourbakis, N.: A survey of skin-color modeling and detection methods. Pattern Recogn. 40(3), 1106–1122 (2007)
Liensberger, C., Stöttinger, J., Kampel, M.: Color-based skin detection and its application in video annotation
Lopes, A.P.B., de Avila, S.E.F., Peixoto, A.N.A., Oliveira, R.S., Coelho, M.D.M, Araujo, A.D.A.: Nude detection in video using bag-of-visual-features. In: 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI), pp. 224–231. IEEE (2009)
Lopes, A.P.B., de Avila, S.E.F., Peixoto, A.N.A., Oliveira, R.S., Araujo, A.D.A.: A bag-of-features approach based on hue-sift descriptor for nude detection. In: 2009 17th European Signal Processing Conference, pp. 1552–1556. IEEE (2009)
Satheesh, P., Srinivas, B., Sastry, R.V.L.S.N.: Pornographic image filtering using skin recognition methods (2012)
Truong, B.T., Venkatesh, S.: Video abstraction: a systematic review and classification. ACM Trans. Multimedia Comput. Commun. Appl. (TOMM) 3(1), 3 (2007)
Van De Sande, K.E.A., Gevers, T., Snoek, C.G.M.: Evaluating color descriptors for object and scene recognition. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1582–1596 (2010)
Wang, D., Zhu, M., Yuan, X., Qian, H.: Identification and annotation of erotic film based on content analysis. In: Photonics Asia 2004, pp. 88–94. International Society for Optics and Photonics (2005)
Yusoff, Y., Christmas, W.J., Kittler, J.: Video shot cut detection using adaptive thresholding. In: BMVC, pp. 1–10 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-26561-2_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26560-5
Online ISBN: 978-3-319-26561-2
eBook Packages: Computer ScienceComputer Science (R0)