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  • 标题:Anti-Spoofing Techniques in Face Recognition, an Ensemble Based Approach
  • 本地全文:下载
  • 作者:Răzvan-Daniel ALBU ; Cornelia Emilia GORDAN ; Ioan DZIȚAC
  • 期刊名称:Studies in Informatics and Control Journal
  • 印刷版ISSN:1220-1766
  • 出版年度:2019
  • 卷号:28
  • 期号:1
  • 页码:111-118
  • DOI:10.24846/v28i1y201912
  • 出版社:National Institute for R&D in Informatics
  • 摘要:In this article we describe the implementation of a reliable and innovative ensemble-based technique that can prevent face spoofing attacks. The presented software is part of a technology developed in partnership with IsItYou, an Israeli company, that attempts to replace passwords with a face-based authentication system. Since the main problem of biometric systems is represented by the spoof attacks, IsItYou came with a solution to this, developing a unique technology that can identify spoof attacks, and authenticate only authorized humans. Inspired from deep learning techniques where ensemble-based solutions improve machine learning results by uniting several models, a software ensemble that combines multiple anti-spoofing methods, covering a larger range of spoof attacks and increasing overall security was developed. The article also shows the performances results and implementation details. The experimental results signpost our solution can provide first-rate results compared to the state-of-the-art approaches.
  • 关键词:Face anti;spoofing; Face recognition; Beware; Biometric security; Ensemble system
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