Ring-a-Pose：用于连续手部姿态追踪的戒指
Ring-a-Pose: A Ring for Continuous Hand Pose Tracking
AI总结：
本文提出单一无系留戒指Ring-a-Pose，通过发射听不见的声学信号并分析反射来追踪连续3D手部姿态与微手势，在零训练数据下关节误差达14.1mm，为低功耗智能戒指手部追踪提供新方案。
摘要：
我们提出了Ring-a-Pose，一种追踪连续3D手部姿态的单一无系留戒指。该戒指位于手部中心，会发射一种人耳听不见的声学信号，每种手部姿态对其的反射方式各不相同。与多戒指或手套系统不同，Ring-a-Pose对手部造成的阻碍极小。它不受可能覆盖腕戴式系统的衣物选择影响。在总共30名参与者参与的三项用户研究中，我们评估了Ring-a-Pose在姿态追踪和微手指手势识别方面的性能。在未从用户处收集任何训练数据的情况下，Ring-a-Pose追踪连续手部姿态的关节误差为14.1mm。对于经过微调的用户相关模型，关节误差降至10.3mm。Ring-a-Pose识别7类微手势，在用户无关和用户相关模型中分别达到90.60%和99.27%的准确率。此外，该戒指戴在任何手指上时均表现出良好的性能。Ring-a-Pose为未来智能戒指利用相对低功耗的声学传感来追踪和识别手部姿态奠定了基础。
英文摘要：
We present Ring-a-Pose, a single untethered ring that tracks continuous 3D hand poses. Located in the center of the hand, the ring emits an inaudible acoustic signal that each hand pose reflects differently. Ring-a-Pose imposes minimal obtrusions on the hand, unlike multi-ring or glove systems. It is not affected by the choice of clothing that may cover wrist-worn systems. In a series of three user studies with a total of 30 participants, we evaluate Ring-a-Pose's performance on pose tracking and micro-finger gesture recognition. Without collecting any training data from a user, Ring-a-Pose tracks continuous hand poses with a joint error of 14.1mm. The joint error decreases to 10.3mm for fine-tuned user-dependent models. Ring-a-Pose recognizes 7-class micro-gestures with a 90.60% and 99.27% accuracy for user-independent and user-dependent models, respectively. Furthermore, the ring exhibits promising performance when worn on any finger. Ring-a-Pose enables the future of smart rings to track and recognize hand poses using relatively low-power acoustic sensing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
