IEEE Trans Image Process. 2015 Mar;24(3):1060-75. doi: 10.1109/TIP.2015.2395951.
The vulnerability of face recognition systems isa growing concern that has drawn the interest from both academic and research communities. Despite the availability of a broad range of face presentation attack detection (PAD)(or countermeasure or antispoofing) schemes, there exists no superior PAD technique due to evolution of sophisticated presentation attacks (or spoof attacks). In this paper, we present a new perspective for face presentation attack detection by introducing light field camera (LFC). Since the use of a LFC can record the direction of each incoming ray in addition to the intensity, it exhibits an unique characteristic of rendering multiple depth(or focus) images in a single capture. Thus, we present a novel approach that involves exploring the variation of the focus between multiple depth (or focus) images rendered by the LFC that in turn can be used to reveal the presentation attacks. To this extent, we first collect a new face artefact database using LFC that comprises of 80 subjects. Face artefacts are generated by simulating two widely used attacks, such as photo print and electronic screen attack. Extensive experiments carried out on the light field face artefact database have revealed the outstanding performance of the proposed PAD scheme when benchmarked with various well established state-of-the-art schemes.
人脸识别系统的脆弱性日益引起学术界和研究界的关注。尽管有广泛的面部呈现攻击检测（PAD）（或对策或反欺骗）方案，但由于复杂的呈现攻击（或欺骗攻击）的发展，不存在优越的 PAD 技术。在本文中，我们通过引入光场相机（LFC）为面部呈现攻击检测提供了新的视角。由于 LFC 的使用除了强度之外还可以记录每个入射光线的方向，因此它具有在单个捕获中呈现多个深度（或焦点）图像的独特特征。因此，我们提出了一种新方法，涉及探索由 LFC 呈现的多个深度（或焦点）图像之间的焦点变化，这反过来又可以用于揭示呈现攻击。在这方面，我们首先使用 LFC 收集了一个包含 80 个主题的新的人脸伪影数据库。人脸伪影是通过模拟两种广泛使用的攻击（例如照片打印和电子屏幕攻击）生成的。在光场人脸伪影数据库上进行的广泛实验表明，所提出的 PAD 方案在与各种成熟的最先进方案进行基准测试时表现出色。
