Covert photo classification by deep convolutional neural networks
作者: Haiqiang ZuoHaitao LangErik BlaschHaibin Ling
作者单位: 1China University of Petroleum
2Temple University
3Beijing University of Chemical Technology
4Air Force Research Lab
刊名: Machine Vision and Applications, 2017, Vol.28 (5-6), pp.623-634
来源数据库: Springer Nature Journal
DOI: 10.1007/s00138-017-0859-x
关键词: Privacy protectionCovert photographyImage classificationVisual attributeDeep convolutional neural networks
英文摘要: The increasing presence of image/video capture devices such as camera phones and surveillance cameras has become a ubiquitous element of providing convenience and improving security in modern life. On the other hand, the pervasiveness of such image/video capture devices raises growing privacy concerns. In this paper, we concentrate on a new visual privacy protection problem—covert photo classification. Covert photography means that the subject being photographed is purposely made unaware that he or she is photographed. A covert photo often contains information that is inherently sensitive and private to a person. If such photos are released on the public without approval, it may lead to serious negative consequences. We explore deep convolutional neural networks (DCNNs) to discover...
原始语种摘要: The increasing presence of image/video capture devices such as camera phones and surveillance cameras has become a ubiquitous element of providing convenience and improving security in modern life. On the other hand, the pervasiveness of such image/video capture devices raises growing privacy concerns. In this paper, we concentrate on a new visual privacy protection problem—covert photo classification. Covert photography means that the subject being photographed is purposely made unaware that he or she is photographed. A covert photo often contains information that is inherently sensitive and private to a person. If such photos are released on the public without approval, it may lead to serious negative consequences. We explore deep convolutional neural networks (DCNNs) to discover...
全文获取路径: Springer Nature  (合作)
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来源刊物:
影响因子:1.103 (2012)

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关键词翻译
关键词翻译
  • convolutional 卷积
  • neural 神经系统的
  • privacy 秘密
  • photo 光电
  • feature 结构元件
  • classification 分类
  • attribute 属性
  • covert 隐藏的
  • camera 摄影机
  • demonstrate 说明