Paper Info
Title
SafeVchat: detecting obscene content and misbehaving users in online video chat services
Abstract
Online video chat services such as Chatroulette, Omegle, and vChatter that randomly match pairs of users in video chat sessions are fast 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 paper presents SafeVchat, a novel solution to the problem of flasher detection that employs an array of image detection algorithms. A key contribution of the paper concerns how the results of the individual detectors are fused together into an overall decision classifying the user as misbehaving or not, based on Dempster-Shafer Theory. The paper 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 Chatroulette.com.
Year
DOI
Venue
2011
10.1145/1963405.1963501
WWW
Keywords
Field
DocType
dempster shafer theory
World Wide Web,Image detection,Computer science,Online video,Recall,Multimedia
Journal
Volume
Citations 
PageRank 
abs/1101.3
11
0.68
References 
Authors
15
9
Name
Order
Citations
PageRank
Xinyu Xing137035.71
Yu-Li Liang2242.69
Hanqiang Cheng3293.48
Jianxun Dang4273.34
Sui Huang5161.58
Richard Han62771200.83
Xue Liu73058193.41
Lv Qin8111691.95
shivakant mishra91521138.23