Action Recognition System for Senior Citizens Using Depth Image Colorization
Ye Htet, Thi Thi Zin, Hiroki Tamura, Kazuhiro Kondo, Etsuo Chosa · 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech) · 2022
This paper describes about the system which can be used at the care center for the purpose of elderly action recognition using depth camera. The depth image colorization is used for compression, visualization, and person detection process. The YOLOv5 (You Only Look Once) algorithm is used as object detector. The space-time features are extracted from depth sequences and they are recognized by linear SVM (Support Vector Machine) classifier. The random image sequences are generated for testing to recognize six actions. The results show that this system can detect the various actions with the average of 92% accuracy for different durations.