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The Security-Utility Trade-off for Iris Authentication and Eye Animation for Social Virtual Avatars

机译:用于社交虚拟化身的虹膜身份验证和眼睛动画的安全实用工具折衷

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The gaze behavior of virtual avatars is critical to social presence and perceived eye contact during social interactions in Virtual Reality. Virtual Reality headsets are being designed with integrated eye tracking to enable compelling virtual social interactions. This paper shows that the near infra-red cameras used in eye tracking capture eye images that contain iris patterns of the user. Because iris patterns are a gold standard biometric, the current technology places the user's biometric identity at risk. Our first contribution is an optical defocus based hardware solution to remove the iris biometric from the stream of eye tracking images. We characterize the performance of this solution with different internal parameters. Our second contribution is a psychophysical experiment with a same-different task that investigates the sensitivity of users to a virtual avatar's eye movements when this solution is applied. By deriving detection threshold values, our findings provide a range of defocus parameters where the change in eye movements would go unnoticed in a conversational setting. Our third contribution is a perceptual study to determine the impact of defocus parameters on the perceived eye contact, attentiveness, naturalness, and truthfulness of the avatar. Thus, if a user wishes to protect their iris biometric, our approach provides a solution that balances biometric protection while preventing their conversation partner from perceiving a difference in the user's virtual avatar. This work is the first to develop secure eye tracking configurations for VR/AR/XR applications and motivates future work in the area.
机译:虚拟化身的凝视行为对于在虚拟现实中的社交互动期间对社会存在和感知的眼睛接触至关重要。虚拟现实耳机正在设计具有集成的眼跟踪,以实现引人注目的虚拟社交交互。本文展示了用于眼部跟踪捕获眼镜的近近红外摄像机,其包含用户的虹膜模式。由于虹膜图案是金标准生物识别,所以当前技术将用户的生物识别身份置于风险。我们的第一种贡献是一种基于光学散焦的硬件解决方案,可以从眼睛追踪图像流中移除虹膜生物识别。我们以不同的内部参数表征了该解决方案的性能。我们的第二个贡献是一个有效的实验,具有同样不同的任务,在应用该解决方案时,将用户的敏感性调查到虚拟头像的眼球运动。通过导出检测阈值,我们的发现提供了一系列散焦参数,其中眼睛运动的变化将在会话设置中被忽视。我们的第三种贡献是一种感知研究,以确定散焦参数对听觉的眼球接触,注意力,自然和真实性的影响。因此,如果用户希望保护其虹膜生物识别,我们的方法提供了一个解决生物识别保护的解决方案,同时防止他们的对话伙伴感知用户的虚拟化身的差异。这项工作是第一个为VR / AR / XR应用开发安全的眼睛跟踪配置,并激励该地区的未来工作。

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