论文标题
这是谁的手？以自我为中心的手势的人身份证
Whose hand is this? Person Identification from Egocentric Hand Gestures
论文作者
论文摘要
通过面孔和其他生物识别技术认识人，已经在计算机视觉中进行了广泛的研究。但是，这些技术不适用于识别以自我为中心（第一人称）相机的佩戴者，因为该人很少（如果有的话）出现在自己的第一人称视角中。但是，尽管自己的脸并不经常可见，但他们的手是：实际上，手是自己的视野中最常见的对象之一。因此，很自然地询问人们手的外观和运动模式是否足以识别它们。在本文中，我们系统地研究了以不受限制的以自我为中心的手势的以自我为中心的手识别（EHI）的可能性。我们探索几种不同的视觉提示，包括颜色，形状，皮肤纹理和深度图，以识别用户的手。进行了广泛的消融实验，以分析最独特的手的特性。最后，我们表明EHI可以通过对抗性训练这些模型来忽略用户之间的差异，从而改善其他任务（例如手势识别）的概括。
Recognizing people by faces and other biometrics has been extensively studied in computer vision. But these techniques do not work for identifying the wearer of an egocentric (first-person) camera because that person rarely (if ever) appears in their own first-person view. But while one's own face is not frequently visible, their hands are: in fact, hands are among the most common objects in one's own field of view. It is thus natural to ask whether the appearance and motion patterns of people's hands are distinctive enough to recognize them. In this paper, we systematically study the possibility of Egocentric Hand Identification (EHI) with unconstrained egocentric hand gestures. We explore several different visual cues, including color, shape, skin texture, and depth maps to identify users' hands. Extensive ablation experiments are conducted to analyze the properties of hands that are most distinctive. Finally, we show that EHI can improve generalization of other tasks, such as gesture recognition, by training adversarially to encourage these models to ignore differences between users.
