Lightweight Fall Detection Algorithm Based on AlphaPose Optimization Model and ST-GCN

Table 5

The influence of mosaic data enhancement method on target recognition accuracy under different proportions.

Algorithm type	m1 : m4 : m9	Dim light (%)	Chaotic environment mAP (%)	Human body occlusion mAP (%)
Algorithm in this paper	1 : 0 : 0	72.28	71.54	75.55
	0 : 1 : 0	60.11	65.58	66.18
	0 : 0 : 1	41.74	50.69	50.10
	1 : 1 : 0	72.45	71.99	75.10
	1 : 0 : 1	70.71	70.24	73.56
	1 : 1 : 1	72.19	71.58	76.01
	2 : 2 : 1	76.28	76.68	78.10
	2 : 1 : 1	72.27	70.44	73.56
	3 : 2 : 1	72.78	72.57	76.15
	4 : 2 : 1	73.35	72.16	74.20
	4 : 3 : 2	72.80	72.01	75.98
	5 : 3 : 2	74.01	74.48	77.52
YOLOv4	1 : 1 : 0	75.90	75.56	76.14