Human Posture Recognition Algorithm for Low-Quality Laser Through-Window Images

Fig. 9. Human posture recognition system for airborne laser through-window imaging. (a) Ground control terminal; (b) Jetson NX development board and wireless transmission equipment; (c) laser through-window imaging system; (d) airborne laser through-window imaging system

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Fig. 10. Schematic diagram of the airborne laser through-window imaging human posture recognition system

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Table 1. Training parameter setting
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Table 1. Training parameter setting
Parameter Setting
Optimizer AdamW
Epochs 200
Batchsize 16
Workers 8
Imgs 640
lr0 0.01
lrf 0.01
Weight_decay 0.0005
Momentum 0.937
Warmup_epochs 3
Warmup_momentum 0.8
Close_mosaic 10

Table 2. Contrast experiment

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Table 2. Contrast experiment

Model	Precision /%	Recall /%	mAP@0.5 /%	mAP@0.5：0.95 /%	Time /ms	Model size /MB
Faster R-CNN	63.1	58.3	61.3	50.5	93.2	110.28
Alphapose	68.9	59.1	65.2	55.8	38.5	158.81
Openpose			57.1	42.2	100.9	204.41
HigherHRNet			62.3	51.4	42.3	109.12
YOLOv5s6-pose	78.8	66.2	64.3	55.2	33.4	25.10
YOLOv8n-Pose	73.9	64.3	62.8	52.4	23.7	6.51
Ours	93.2	90.9	78.8	62.5	18.6	4.82

Table 3. Ablation experimental results

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Table 3. Ablation experimental results

Model	Precision /%	Recall /%	mAP@0.5 /%	mAP@0.5：0.95 /%	Time /ms	Model size /MB
1	73.9	64.3	62.8	52.4	23.7	6.51
2	77.3	68.5	65.2	54.6	24.1	6.60
3	78.6	74.0	67.7	55.3	16.4	4.81
4	85.5	79.1	70.7	58.8	27.3	7.00
5	84.2	77.2	70.1	60.2	18.2	4.60
6	92.3	90.3	78.8	62.5	18.6	4.82
7	93.2	90.9	78.8	62.5	18.6	4.82

Table 4. Algorithm verification
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Table 4. Algorithm verification
Pose Quantity True quantity False quantity Accuracy /%
Single pose Standing 3645 3485 160 95.6
Squatting 2185 2012 173 92.1
Creeping 2565 2211 354 86.2
Multiple poses 2262 1914 348 84.6
Total 10657 9622 1035 90.3

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Zhihua Wu, Jianghua Cheng, Tong Liu, Yahui Cai, Lehao Pan. Human Posture Recognition Algorithm for Low-Quality Laser Through-Window Images[J]. Chinese Journal of Lasers, 2025, 52(6): 0609002

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