User-generated Pornographic Video Detection Using Shot-based Sensor Pattern Noise

Illegal distribution of user-generated pornography (UGP) videos raises lots of negative aspects associated with the digital contents. This paper proposes a first forensic technique to detect UGP video. To discriminate UGP videos, we exploit shot based sensor pattern noise (SPN) from an image under investigation. By thresholding average peakto-correlation (PCE) values from the shot based SPNs, the video is decided as a UGP video. Preliminary experiments, which consist of UGP videos, normal videos, and Japanese commercial pornographic videos, indicate adequate performance of the proposed technique.