Safe V chat: A system for obscene content detection in online video chat services

Yu Li Liang, Xinyu Xing, Hanqiang Cheng, Jianxun Dang, Sui Huang, Richard Han, Xue Liu, Qin Lv, Shivakant Mishra

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Online video chat services such as Chatroulette, Omegle, and vChatter that randomly match pairs of users in video chat sessions are quickly becoming very popular, with over a million users per month in the case of Chatroulette. A key problem encountered in such systems is the presence of flashers and obscene content. This problem is especially acute given the presence of underage minors in such systems. This article presents SafeVchat, a novel solution to the problem of flasher detection that employs an array of image detection algorithms. A key contribution of the article concerns how the results of the individual detectors are fused together into an overall decision classifying a user as misbehaving or not, based on Dempster- Shafer theory. The article introduces a novel, motion-based skin detection method that achieves significantly higher recall and better precision. The proposed methods have been evaluated over real-world data and image traces obtained from SafeVchat has been deployed in Chatroulette. A combination of SafeVchat with human moderation has resulted in banning as many as 50,000 inappropriate users per day on Chatoulette. Furthermore, offensive content on Chatoulette has dropped significantly from 33.08% (before SafeVchat installation) to 3.49% (after SafeVchat installation).

Original languageEnglish (US)
Article number2499927
JournalACM Transactions on Internet Technology
Issue number4
StatePublished - Jul 2013

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


Dive into the research topics of 'Safe V chat: A system for obscene content detection in online video chat services'. Together they form a unique fingerprint.

Cite this