Human Action Recognition based on LSTM Model using Smartphone Sensor
| Autor: | Young Bok Choi, Yull Kyu Han |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Deep learning 020208 electrical & electronic engineering Gyroscope 02 engineering and technology law.invention Acceleration Order (business) law 0202 electrical engineering electronic engineering information engineering Action recognition 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | ICUFN |
| DOI: | 10.1109/icufn.2019.8806065 |
| Popis: | We propose a deep learning model for human action recognition in order to quickly detect occurrence of disasters such as fire and terrorism. Using the acceleration and gyroscope sensors built in the smartphone, four kinds of data on human behavior were obtained and human behavior was classified through the LSTM deep learning model. As an experiment, it was confirmed that the LSTM model can be classified 95.47% accurately. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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