Human Pose Estimation Model Based on Improved Hourglass Network

Fig. 5. Experimental results of different methods on the COCO data set. (a) DeepPose^[11]; (b) CPM^[12]; (c) 8-SHN^[13]; (d) Baseline^[19]; (e) IHN-OHKM

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Fig. 6. AP curves for different methods in COCO data set

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Fig. 7. Detection results of our method on the COCO data set

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Table 1. Test results of different methods on the COCO data set unit: %

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Table 1. Test results of different methods on the COCO data set unit: %

Method	AP	AP^@50	AP^@75	AP^@m	AP^@l	AR
DeepPose^[11]	66.5	80.6	73.6	63.4	72.7	71.9
CPM^[12]	66.9	82.3	76.3	65.3	75.9	74.4
8-SHN^[13]	69.4	85.3	79.8	67.4	78.6	76.8
Baseline^[19]	72.9	88.5	80.2	69.0	79.3	78.2
IHN	73.6	88.7	80.5	69.1	79.0	79.1
IHN-OHKM	74.5	88.8	80.2	69.4	78.5	79.6

Table 2. Calculation efficiency of different methods
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Table 2. Calculation efficiency of different methods
Method Average processing time /ms GFLOPs /(10⁹ times) Number of parameters
8-SHN^[13] 66 20.3 4.6×10⁷
IHN 20 6.4 1.3×10⁷
IHN-OHKM 23 6.9 1.5×10⁷

Table 3. Test results of different methods on MPII data set unit: %

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Table 3. Test results of different methods on MPII data set unit: %

Method	Head	Sho.	Elb.	Wri.	Hip.	Knee	Ank.	Mean
DeepPose^[11]	95.4	94.3	91.7	84.0	89.7	87.0	81.3	89.1
CPM^[12]	96.2	95.0	92.0	84.9	90.5	87.7	82.0	89.8
8-SHN^[13]	97.6	95.7	92.3	85.3	91.3	88.6	82.5	90.5
Baseline^[19]	97.0	96.5	93.4	88.5	92.0	90.7	83.2	91.8
IHN	97.3	97.8	94.2	89.0	92.6	90.5	85.9	92.5
IHN-OHKM	97.0	98.9	95.3	88.6	94.0	90.2	86.4	92.9

Table 4. Ablation experiments on the COCO validation data set
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Table 4. Ablation experiments on the COCO validation data set
Residual module layer Deconvolution layer AP /% Average processing time /ms
3 2 71.2 16.6
4 3 74.6 18.0
5 4 75.0 21.4

Table 5. Impact of different M on AP
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Table 5. Impact of different M on AP
M 6 8 10 12 14 17
AP /% 70.4 75.5 74.1 73.0 72.7 72.5

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Hong Liu, Jie Ma, Yujing Chai. Human Pose Estimation Model Based on Improved Hourglass Network[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2015004

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