This article aims to present a novel sensor-based continuous hand gesture recognition algorithm by long short-term memory (LSTM). Only the basic accelerators and/or gyroscopes are required by the algorithm. Given a sequence of input sensory data, a many-to-many LSTM scheme is adopted to produce an output path. A maximum a posteriori estimation is then carried out based on the observed path to obtain the final classification results. A prototype system based on smartphones has been implemented for the performance evaluation. Experimental results show that the proposed algorithm is an effective alternative for robust and accurate hand-gesture recognition.
@article{arxiv.2007.11268,
title = {Sensor-Based Continuous Hand Gesture Recognition by Long Short-Term Memory},
author = {Tsung-Ming Tai and Yun-Jie Jhang and Zhen-Wei Liao and Kai-Chung Teng and Wen-Jyi Hwang},
journal= {arXiv preprint arXiv:2007.11268},
year = {2020}
}