HCC-SMALL: High-Resolution RFID Tracking With Applications In Gesture Recognition And Human-Computer Interaction

目前的手势识别工作，如基于视觉和直接感知的方法，尚未被证明是有效和实用的。同样，人机交互（HCI）方法，尽管有相当大的研究努力，仍然由传统的键盘和鼠标主导。改进HCI是一个关键的需求领域，特别是对于那些发现传统方法繁琐（往好了说）或无法使用（往坏了说）的残疾人而言。射频识别（RFID）技术的快速发展具有显著推进当前手势识别和人机交互挑战的潜力。RFID方法的优点包括无源标签的小型化，安全植入标签的能力，以及远程跟踪多个标签的潜力；这些特征结合起来支持基于（标记的）人类动作或手势的界面的定义、识别和开发。PI在这个项目中的目标是为最具挑战性的手势识别和人机交互应用探索RFID解决方案，包括复杂的手势识别和为严重运动障碍的个人提供有效的计算机接口。这些目标将通过一系列协调的研究、开发和评估工作来实现。首先，RFID定位算法将利用谐波雷达方法开发，并使用改进的商用组件实现；这种方法将比目前的功耗技术产生更高的分辨率，并且能够在经济有效的实施中跟踪多个标签。接下来，将执行小型和大型工作空间的实现。小型工作空间的实现将解决严重残疾人士基于舌头的人机交互问题，而大型工作空间的实现将用于手势识别和计算机控制。最后，将严格评估算法、硬件和实现的基本准确性、应用程序性能和用户效能。基本的准确性评估将描述时空RFID标签跟踪的性能和局限性，而人机交互和手势识别能力将通过应用性能和用户效能评估来评估。更广泛的影响：本研究从根本上解决了残疾人面临的重要接口和沟通问题，并将包括残疾人直接参与的项目。项目成果将为残疾人提供更有效的接口和更强的通信能力，从而提供更大的独立性，并最终改善社会、教育和经济机会。为了实现这些目标，该项目将为一种全新的方法奠定基础，以捕捉、表征和利用HCI和手势识别应用中的人类运动。该结果将对目标应用产生重大影响，例如动物研究，人类表现研究，甚至安全（例如，监测物体的细微运动）。

Current gesture recognition efforts, such as vision and direct sensing based methods, are yet to be proven effective and practical. Similarly, human-computer interaction (HCI) methods, despite considerable research efforts, remain dominated by the traditional keyboard and mouse. Improving HCI is a critical area of need, especially for individuals with disabilities who find traditional methods cumbersome (at best) or unusable (at worst). The rapid development of radio frequency identification (RFID) technologies holds the potential to significantly advance current challenges in both gesture recognition and HCI. Advantages of RFID approaches include miniaturization of passive tags, the ability to safely implant tags, and the potential to remotely track multiple tags; these characteristics combine to support the definition, recognition, and development of interfaces based on (tagged) human movements, or gestures. The PI's goal in this project is to explore RFID solutions for the most challenging gesture recognition and HCI applications, including complex gesture recognition and effective computer interfaces for individuals with severe motor impairments. These objectives will be realized through a series of coordinated research, development, and evaluation efforts. First, RFID localization algorithms will be developed utilizing harmonic radar approaches and implemented using modified commercially available components; this approach will yield significantly higher resolution than current power loss techniques, and will be capable of tracking multiple tags in cost-effective implementations. Next, implementations for small and large workspace will be carried out. The small workspace implementation will address tongue-based HCI for individuals with severe disabilities, while the large workspace implementation will be used for hand gesture recognition and computer control. Finally, the algorithms, hardware, and implementations will be rigorously evaluated for fundamental accuracy, application performance, and user efficacy. Fundamental accuracy evaluations will characterize the performance and limits of spatial-temporal RFID tag tracking, while HCI and gesture recognition capabilities will be assessed through application performance and user efficacy evaluations. Broader Impacts: This research addresses fundamentally important interface and communications issues faced by individuals with disabilities, and will include direct programmatic involvement by individuals with disabilities. Project outcomes will afford individuals with disabilities more effective interfaces and greater communications capabilities, thereby providing greater independence and, ultimately, improved social, educational, and economic opportunities. In achieving these objectives, the project will lay the foundation for a fundamentally new approach to capturing, characterizing, and exploiting human movement for HCI and gesture recognition applications. The results will have significant impact beyond the targeted applications, for instance in animal studies, human performance studies, and even security (e.g., monitoring fine movements of objects).