The Combination of Face Identification and Action Recognition for Fall Detection
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Author
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Ngu D. DaoThe University of Danang - University of Science and TechnologyThien V. LeThe University of Danang - University of Science and TechnologyHanh T. M. TranThe University of Danang - University of Science and TechnologyYen T. H. NguyenThe University of Danang - University of Science and TechnologyTuan D. DuyThe University of Danang - University of Science and Technology
Từ khóa:
Face recognition
action recognition
skeleton detection
Spatial Temporal Graph Convolutional Network
Long Short-Term Memory
Tóm tắt
Falls are a very common unexpected accident that result in serious injuries such as broken bones, head injury. Detecting falls, taking fall patients to the emergency room, and sending notification to their family in time is very important. In this paper, we propose a method that combines face recognition and action recognition for fall detection. Specifically, we identify seven basic actions that take place in elderly daily life based on skeleton data extracted using YOLOv7-Pose model. Two deep models which are Spatial Temporal Graph Convolutional Network (ST-GCN), and Long Short-Term Memory (LSTM) are employed for action recognition on the skeleton data. The experimental results on our dataset show that ST-GCN model achieved an accuracy of 90% that is 7% higher than the LSTM model.
Tài liệu tham khảo
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Cách trích dẫn
D. Dao, N., T. V. Le, H. T. M. Tran, Y. T. H. Nguyen, và T. D. Duy. “The Combination of Face Identification and Action Recognition for Fall Detection”. Tạp Chí Khoa học Và Công nghệ - Đại học Đà Nẵng, vol 20, số p.h 12.2, Tháng Chạp 2022, tr 37-44, doi:10.31130/ud-jst.2022.539ICT.
