Preliminary Investigation of Fine-Grained Gesture Recognition With Signal Super-Resolution

Preliminary Investigation of Fine-Grained Gesture Recognition With Signal Super-Resolution
复制标题

DOI：
10.1109/percomw.2018.8480357
复制
发表时间：
2018-03
期刊：
2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
影响因子：
--
通讯作者：
Naoya Yoshimura;T. Maekawa;Daichi Amagata;T. Hara
Naoya Yoshimura;T. Maekawa;Daichi Amagata;T. Hara
中科院分区：
其他
文献类型：
--
作者：
Naoya Yoshimura;T. Maekawa;Daichi Amagata;T. Hara

文献摘要

相似文献

本研究探讨了使用上采样加速度传感器数据进行细粒度手势识别的可行性。由于智能手表设备的最大采样率受到操作系统的限制，我们使用神经网络从低分辨率信号模拟高分辨率加速度数据，以捕捉包含高频分量的手势的区别特征。
This study investigates the feasibility of fine-grained gesture recognition using upsampled acceleration sensor data. Because the maximum sampling rate of smartwatch devices is limited by operating systems, we simulate high resolution acceleration data using a neural network from low resolution signals in order to capture distinguishing features of gestures containing high frequency components.