Preliminary Investigation of Fine-grained Gesture Recognition with Signal Super-resolution

被引：0
|
作者：
Yoshimura, Naoya [1 ]
Maekawa, Takuya [1 ]
Amagata, Daich [1 ]
Hara, Takahiro [1 ]
机构：
[1] Osaka Univ, Suita, Osaka, Japan
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS) | 2018年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页数：4
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