Feature Based Human Activity Recognition using Neural Network
| Autor: | Bawin Aye, Myo Min Hein, Win Myat Oo |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
education.field_of_study
Artificial neural network Computer science business.industry Population Feature extraction Feature selection Machine learning computer.software_genre Object (computer science) Bridge (nautical) Activity recognition Support vector machine Artificial intelligence education business computer |
| Zdroj: | 2020 International Conference on Advanced Information Technologies (ICAIT). |
| DOI: | 10.1109/icait51105.2020.9261774 |
| Popis: | In various research areas, human activity recognition system (HAR) becomes more popular. Features is one of the important things to recognize the object or activity in machine learning. Increasing the old age population in our country, the smart nursing home monitoring and heath care supporting system is still needed to develop. The dataset for experiment is collected from 'Cherry Myay' nursing home in Pyin Oo Lwin, Myanmar. We proposed new feature extraction method, new morphological operation method 'Vertical Binary Bridge' pose classification method using SVM and new frequency based feature selection method. Artificial neural network is used to recognize the human activity and abnormal behaviour detection system. Compared with other exiting methods, our proposed system can achieve acceptable result. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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