With the establishment of Industry 4.0 , machines are now required to interact with workers. By observing biometrics they can assess if humans are authorized, or mentally and physically fit to work. Understanding body language, makes human–machine interaction more natural, secure, and effective. Nonetheless, traditional cameras have limitations; low frame rate and dynamic range hinder a comprehensive human understanding. This poses a challenge, since faces undergo frequent instantaneous microexpressions. In addition, this is privacy-sensitive information that must be protected. We propose to model expressions with event cameras, bio-inspired vision sensors that have found application within the Industry 4.0 scope. They capture motion at millisecond rates and work under challenging conditions like low illumination and highly dynamic scenes. Such cameras are also privacy-preserving, making them extremely interesting for industry. We show that using event cameras, we can understand human reactions by only observing facial expressions. Comparison with red-green-blue (RGB)-based modeling demonstrates improved effectiveness and robustness.

中文翻译：

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了解使用事件相机观察面部微表情的人类反应

随着成立工业 4.0，机器现在需要与工人互动。通过观察生物特征，他们可以评估人类是否被授权，或者在精神上和身体上是否适合工作。理解肢体语言，使人机交互更加自然、安全和有效。尽管如此，传统相机还是有局限性。低帧率和动态范围阻碍了人类的全面理解。这提出了一个挑战，因为面部经常会经历瞬时的微表情。此外，这是必须保护的隐私敏感信息。我们建议使用已在工业 4.0 范围内找到应用的事件相机、仿生视觉传感器对表达式进行建模。它们以毫秒的速度捕捉运动，并在低照度和高动态场景等具有挑战性的条件下工作。这样的相机还可以保护隐私，这使得它们对工业界来说非常有趣。我们表明，使用事件相机，我们可以仅通过观察面部表情来了解人类的反应。与基于红-绿-蓝 (RGB) 的建模的比较证明了改进的有效性和鲁棒性。