Content-based adult video detection plays an important role in preventing pornography. However, existing methods usually rely on single modality and seldom focus on multi-modality semantics representation. Addressing at this problem, we put forward an approach of analyzing periodicity and saliency for adult video detection. At first, periodic patterns and salient regions are respective-ly analyzed in audio-frames and visual-frames. Next, the multi-modal co-occurrence semantics is described by combining audio periodicity with visual saliency. Moreover, the performance of our approach is evaluated step by step. Experimental results show that our approach obviously outper-forms some state-of-the-art methods.
@article{arxiv.1901.03462,
title = {Analyzing Periodicity and Saliency for Adult Video Detection},
author = {Yizhi Liu and Xiaoyan Gu and Lei Huang and Junlin Ouyang and Miao Liao and Liangran Wu},
journal= {arXiv preprint arXiv:1901.03462},
year = {2019}
}