JOURNAL ARTICLE

Gesture Recognition System Based on Neural Networks by Using COTS RFID Tag Array

Abstract

Nowadays, gesture recognition plays a more and more important role in human-computer interaction. In this regard, contact sensors or computer vision have made some progress, but they also have shortcomings in portability or privacy. In this work, we propose a gesture recognition system which uses RFID tag array and neural networks to recognize gestures. By using an RFID tag array, we can obtain gesture information in a non-contact, non-infringing manner. By combining CNN and LSTM as CNN-LSTM, we can focus on both spatial and temporal features and get better performance. Experiments show that the accuracy of the system on the test set is 92.17%, and it performs well in recognizing different gestures of different users at different speeds.

Keywords:
Gesture Computer science Gesture recognition Software portability Focus (optics) Artificial intelligence Set (abstract data type) Artificial neural network Computer vision Speech recognition Pattern recognition (psychology)

Metrics

1
Cited By
0.00
FWCI (Field Weighted Citation Impact)
18
Refs
0.21
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hand Gesture Recognition Systems
Physical Sciences →  Computer Science →  Human-Computer Interaction
Gait Recognition and Analysis
Physical Sciences →  Engineering →  Biomedical Engineering
Human Pose and Action Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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