Fig. 1. Overall flow chart of algorithm

Fig. 2. Architecture of SE block

Fig. 3. Architecture of human pose estimation

Fig. 4. Schematic diagram of partial eigenvalue selection. (a) Some joints and joint angles; (b) body relative position vector

Fig. 5. Training samples (standing). (a) Walking in oblique direction; (b) backward walking; (c) lateral walking; (d) front standing

Fig. 6. Training sample (falling). (a) Front half fall; (b) side half fall; (c) lie; (d) prostration

Fig. 7. Training sample (sitting). (a) Sitting posture of left; (b) sitting posture of right

Fig. 8. Examples of pose estimation results. (a) Fall posture bone detection; (b) sitting posture bone detection; (c) standing posture bone detection; (d) coordinate distribution of 17 joints of standing posture of human body

Fig. 9. First subtree of XGBoost

Fig. 10. Test results of actual scene. (a) Half fall; (b) fall on one side

Fig. 11. Comparison of different algorithms. (a) Algorithm in this paper under the same posture; (b) poor posture detected in Ref. [10]