发表刊物：Cognitive Systems Research
摘要：As the commonest part of social networks, sharing images in social network not only provides more information, but also gives more intuitive view than text. However, images also can leak out information more easily than text, so the audit of image content is particularly essential. The disclosure of a tiny image, which involves sensitive information about individual, society even the state, may trigger a series of serious problems. In this paper, we design a kind of intelligent image firewall to detect and filter sensitive or privacy images. Two different approaches of the firewall are proposed. In the first approach, we propose an image firewall based on joint sparse representation, which can provide accurate and robust privacy prediction, and also can provide rich spatial relationship information. In the second approach, we propose a method based on the deep learning (Faster RCNN), which can predict the privacy relationships or actions (like kiss, hug and hand in hand) among the persons of an image. Experimental results show the effectiveness of the two kinds of approaches.
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：53
页面范围：85-97
是否译文：否
发表时间：2019-01-10