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首页> 外文期刊>International journal of electronics >Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices
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Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

机译：基于运动传感器融合的手势识别及其移动设备的VLSI架构设计

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摘要

With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.
机译：随着智能手机和平板电脑的迅速普及，各种嵌入式传感器已集成到这些平台中，以实现多模式人机界面。手势识别作为一种直观的交互方法，已经在移动计算社区中进行了广泛的探索。但是，到目前为止，大多数手势识别实现都依赖于用户，并且仅依赖于加速度计。为了获得具有竞争力的精度，要求用户在操作过程中以预定的方式握住设备。本文提出了一种基于多运动传感器融合的高精度人体手势识别系统。此外，为了减少由于频繁的传感器采样和数据处理而导致的能量开销，还提出了在Xilinx Virtex-5 FPGA板上实现的高能效VLSI架构。与纯软件实现相比，在20 MHz下运行时，可实现约45倍的加速。实验表明，当受试者在完成指定的手势期间随机握住设备时，与用户无关的情况下10个手势的平均准确度达到93.98％，与用户无关的情况下达到96.14％。尽管比常规最佳结果低几个百分点，但仍提供了实际使用中可接受的竞争准确性。最重要的是，所提出的系统允许用户在操作预定义手势期间随机地握住设备，这大大增强了用户体验。

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  • 来源
    《International journal of electronics》 |2014年第6期|621-635|共15页
  • 作者

    Wenping Zhu; Leibo Liu; Shouyi Yin; Siqi Hu; Eugene Y. Tang; Shaojun Wei;

  • 作者单位

    National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

    Intel Labs, No.2 KeXueYuan South Rd Hadian, Beijing, China;

    National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    gesture recognition; VLSI architecture; motion sensor; DCT; DTW;

    机译：手势识别VLSI架构;运动传感器;DCT;DTW;

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