Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Recognition of adult images, videos, and web page bags

Recognition of adult images, videos, and web page bags Recognition of Adult Images, Videos, and Web Page Bags WEIMING HU, HAIQIANG ZUO, OU WU, and YUNFEI CHEN, Institute of Automation, Chinese Academy of Sciences ZHONGFEI ZHANG, State University of New York DAVID SUTER, University of Adelaide In this article, we develop an integrated adult-content recognition system which can detect adult images, adult videos, and adult Web page bags, where a Web page bag consists of a Web page and a prede ned number of Web pages linked to it through hyperlinks. In our adult image-recognition algorithm, we model skin patches rather than skin pixels, resulting in better results than state-of-the-art algorithms which model skin pixels. In our adult video-recognition algorithm, information from the accompanying audio section around an image in an adult video is used to obtain a prior classi cation of the image. The algorithm achieves a better performance than the ones which use image information alone or audio information alone. The adult Web page bag recognition is carried out using multi-instance learning based on the combination of classifying texts, images and videos in Web pages. Both the speed and the accuracy for recognizing the Web adult content are increased, in contrast to recognizing Web pages http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) Association for Computing Machinery

Recognition of adult images, videos, and web page bags

Download PDF
24 pages

Loading next page...
 
/lp/association-for-computing-machinery/recognition-of-adult-images-videos-and-web-page-bags-0snX0VFkwn
Publisher
Association for Computing Machinery
Copyright
Copyright © 2011 by ACM Inc.
ISSN
1551-6857
DOI
10.1145/2037676.2037685
Publisher site
See Article on Publisher Site

Abstract

Recognition of Adult Images, Videos, and Web Page Bags WEIMING HU, HAIQIANG ZUO, OU WU, and YUNFEI CHEN, Institute of Automation, Chinese Academy of Sciences ZHONGFEI ZHANG, State University of New York DAVID SUTER, University of Adelaide In this article, we develop an integrated adult-content recognition system which can detect adult images, adult videos, and adult Web page bags, where a Web page bag consists of a Web page and a prede ned number of Web pages linked to it through hyperlinks. In our adult image-recognition algorithm, we model skin patches rather than skin pixels, resulting in better results than state-of-the-art algorithms which model skin pixels. In our adult video-recognition algorithm, information from the accompanying audio section around an image in an adult video is used to obtain a prior classi cation of the image. The algorithm achieves a better performance than the ones which use image information alone or audio information alone. The adult Web page bag recognition is carried out using multi-instance learning based on the combination of classifying texts, images and videos in Web pages. Both the speed and the accuracy for recognizing the Web adult content are increased, in contrast to recognizing Web pages

Journal

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) – Association for Computing Machinery

Published: Oct 1, 2011

There are no references for this article.