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环Gesture:一个基于环的空中手势打字系统,由深度学习字预测框架提供动力.

Junxiao Shen, Roger Boldu, Arpit Kalla

    IEEE transactions on visualization and computer graphics
    |September 9, 2024
    PubMed
    概括

    RingGesture是一种基于环的新型系统,可为增强现实 (AR) 眼镜提供高效的空中手势输入. 它通过其先进的Score Fusion文字预测框架实现了高文本输入速度和更高的准确性.

    科学领域:

    • 人与计算机的交互
    • 增强现实是一种增强现实.
    • 可穿戴技术可穿戴技术

    背景情况:

    • 轻量级AR眼镜需要高效的文本输入解决方案,因为相机对手部追踪的能力有限.
    • 现有的输入方法可能不适合全天可穿戴的AR设备.

    研究的目的:

    • 为了介绍RingGesture,一个基于戒指的AR眼镜的空中手势打字系统.
    • 开发和评估Score Fusion词预测框架,以提高准确性和速度.

    主要方法:

    • RingGesture使用电极和惯性测量单元 (IMU) 来进行手势识别和手跟踪.
    • 评分融合框架整合了一个词-手势解码模型,空间拼写纠正,以及一个语境语言模型.

    主要成果:

    • RingGesture的平均文本输入速度为每分钟27.3个单词 (WPM),峰值为每分钟47.9个WPM.
    • 与天真纠正相比,Score Fusion框架提高了未经纠正的字符错误率28.2%,文本输入速度提高了55.2%.
    • RingGesture获得了83的系统可用性评分,表明了卓越的可用性.

    结论:

    • RingGesture提供了一个有效和可用的解决方案,用于在轻量级AR眼镜中输入文本.

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  • 评分融合框架显著提高了空中手势打字系统的性能.