基于cnn的非接触式电梯按钮控制手势识别

Tae-Ho Lee, Vidura Munasinghe, Yan-Mei Li, Tae Sung Kim, Hyuk-Jae Lee
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引用次数: 1

摘要

最近,随着新冠肺炎大流行的爆发,采取了各种隔离措施,以减少病毒的传播。作为努力的一部分,对非接触式技术的偏好已经出现。本文提出了一种基于cnn手势识别的非接触式电梯控制系统。实验结果表明,Jetson TX2板上的手识别AP和FPS分别为81.87%和11.8FPS。我们证明了利用基于cnn的手势识别,可以通过虚拟电梯按钮来控制电梯模型。该方法可应用于商用电梯,作为防止病毒通过电梯按钮传播的一种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CNN-based Hand Gesture Recognition for Contactless Elevator Button Control
Recently, with the outbreak of the COVID-19 pandemic, various quarantine measures have been implemented to reduce the spread of the virus. As a part of efforts, the preference for touchless technology has been emerging. In this paper, we propose a touchless elevator control system using CNN-based hand gesture recognition. Experimental results show that the hand recognition AP and FPS on the Jetson TX2 board are 81.87% and 11.8FPS, respectively. We demonstrate that an elevator model could be controlled by virtual elevator buttons utilizing CNN-based hand gesture recognition. The proposed method can be applied to commercial elevators as an approach to prevent the spread of viruses from elevator buttons.
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