Sewing Gesture Image Detection Method Based on Improved SSD Model

Table 1. Number of images in amplification dataset
View table
Table 1. Number of images in amplification dataset
Category Training Validation Test Total
Cladding sewing 900 290 290 1500
Crimp sewing 840 280 280 1400
Fabric cutting 960 320 320 1600
Knots-makingsewing 780 260 260 1300

Table 2. Recognition results comparison of 4 algorithms
View table
Table 2. Recognition results comparison of 4 algorithms
Mothod mAP /%
VOC NUS-II
YOLO 0.755 0.842
SSD 0.785 0.883
SSD-modified 0.793 0.903

Table 3. Experimental results under different lighting conditions
View table
Table 3. Experimental results under different lighting conditions
Data category Morningbrightness Noonbrightness Nightbrightness
A-F1 score 0.834 0.732 0.763
B-F1 score 0.842 0.825 0.838

Table 4. Comparison of mAP results in ablation experiments%
View table
Table 4. Comparison of mAP results in ablation experiments%
Data augmentation Backbone Feature layer fusion
Original Corrected VGG16 Resnet50 Original Corrected
77.23 85.44 81.35 83.34 80.44 83.28

Table 5. Comparison of recognition results under 4 algorithms

View table

Table 5. Comparison of recognition results under 4 algorithms

Method	AP /%				mAP /%	Small target	Detectionspeed /s^-1
Method	Claddingsewing	Crimpsewing	Fabriccutting	Knots-making sewing	mAP /%	Small target	Detectionspeed /s^-1
Faster R-CNN	88.21	84.56	86.93	83.62	85.83	63.23	13
YOLO	85.22	85.04	77.90	85.48	83.41	57.44	47
SSD	87.34	83.55	84.23	87.48	85.65	55.34	48
RetinaNet	87.39	86.04	87.34	87.96	87.18	65.78	51
SSD-modified	87.21	89.45	88.58	89.52	88.69	67.44	52

Tools

Get Citation

Copy Citation Text

Weiming Yao, Xiaohua Wang, Nan Wu. Sewing Gesture Image Detection Method Based on Improved SSD Model[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181017

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites