基于多频射频传感器网络运动学的ASL识别

S. Gurbuz, A. Gürbüz, E. Malaia, Darrin J. Griffin, Chris S. Crawford, Emre Kurtoğlu, Mohammad Mahbubur Rahman, Ridvan Aksu, Robiulhossain Mdrafi
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引用次数: 4

摘要

作为利用技术在聋人空间设计中的一种手段,本文介绍了使用射频传感的美国手语(ASL)识别的初步结果。射频传感器是非接触式、非侵入性和隐私保护,使其在个人区域使用特别有趣。本文仅利用多频射频传感器网络的微多普勒特征捕捉到的手语运动特性,表明可以以% 99%的准确率区分本地和模仿手势,而识别多达20个美国手语手势的准确率为% 72%或更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASL Recognition Based on Kinematics Derived from a Multi-Frequency RF Sensor Network
As a means for leveraging technology in the design of Deaf spaces, this paper presents initial results on American Sign Language (ASL) recognition using RF sensing. RF sensors are non-contact, non-invasive, and protective of privacy, making them of special interest for use in personal areas. Using just the kinematic properties of signing as captured by the micro-Doppler signatures of a multi-frequency RF sensor network, this paper shows that native and imitation signing can be differentiated with %99 accuracy, while up to 20 ASL signs are recognized with an accuracy of %72 or higher.
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