| Autor: |
Tai, Tsung-Ming, Jhang, Yun-Jie, Liao, Zhen-Wei, Teng, Kai-Chung, Hwang, Wen-Jyi |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
IEEE sensors letters 2.3 (2018): 1-4 |
| Druh dokumentu: |
Working Paper |
| Popis: |
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. |
| Databáze: |
arXiv |
| Externí odkaz: |
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