Development of an Assistive Device via Smart Glasses

Chia-Sui Wang, Wesley Huang, Yih-Feng Chang, Chia-Mao Yeh, Zhi-Yao Xu
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引用次数: 1

Abstract

This study used smart glasses as the carrier to develop three applications aimed at the elderly. Taiwan entered an elderly society in 2018, with the proportion of the elderly population exceeding 14%. It is estimated that the elderly population will exceed 20% in 2026, and Taiwan will enter an ultra-elderly society. To improve the quality of life of the elderly and attach importance to the health care of the elderly, more and more scientific and technological products are used to improve the life and consumption patterns of the elderly, thereby promoting the popularization of smart wearable devices and sensing technologies. In view of the purpose, this research develops related functional applications with smart glasses. First, the memory recall mechanism is carried out based on face recognition. When the user uses the function, an embedded camera in glasses is turned on to capture the target personnel. Afterwards, a KNN (K Nearest Neighbor) machine learning approach is applied to identify the target, and the personal data is performed in the glasses through searching on the developed cloud database. Besides, the user can add, delete and modify the personal data through the computer, which the entrance is carried out by scanning the two-dimension code shown in the computer program with glasses for security purpose. Secondly, the image enhancement function shows that the captured texts can be expanded and enlarged in the projection monitor of glasses. Finally, the construction of voice commands is performed through the microphone within the suite of smart glasses. The results show that the accuracy rate of KNN face recognition is 93.3%, which can be applied to general life situations.
基于智能眼镜的辅助设备的开发
本研究以智能眼镜为载体,开发了三种针对老年人的应用。2018年,台湾进入老年社会,老年人口比例超过14%。预计2026年老年人口将超过20%,台湾将进入超老年社会。为了提高老年人的生活质量,重视老年人的健康护理,越来越多的科技产品被用于改善老年人的生活和消费方式,从而推动了智能可穿戴设备和传感技术的普及。鉴于此,本研究开发了与智能眼镜相关的功能应用。首先,在人脸识别的基础上,建立了记忆回忆机制。当用户使用该功能时,就会打开眼镜内的嵌入式摄像头,捕捉目标人员。然后,采用KNN (K最近邻)机器学习方法对目标进行识别,并在开发的云数据库中进行搜索,在眼镜中执行个人数据。此外,用户还可以通过计算机对个人数据进行添加、删除和修改,为了安全起见,用户需要戴上眼镜扫描计算机程序中显示的二维码。其次,图像增强功能表明,在眼镜投影监视器中,捕获的文本可以进行扩展和放大。最后,语音命令的构建是通过智能眼镜套件内的麦克风进行的。结果表明,KNN人脸识别准确率为93.3%,可应用于一般生活场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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