Laser & Optoelectronics Progress, Volume. 57, Issue 18, 181019(2020)
3D Point Cloud Classification and Segmentation Model Based on Graph Convolutional Network
Figures & Tables(7)
Fig. 2. Neighborhood information of the target node Pi at K=2 aggregated by GraphLayer
Table 1. Classification experimental accuracy
View tableTable 1. Classification experimental accuracy
Model Mean class accuracy /% Overall accuracy /% 3DShapeNets[ 5 ]VoxNet[ 6 ]PointNet[ 8 ]GraphPNet 77.0 83.0 83.7 85.3 84.7 85.9 87.6 89.6
Table 2. Accuracy at different values k
View tableTable 2. Accuracy at different values k
k Mean class accuracy /% Overall accuracy /% 25 30 35 40 45 50 55 85.0 84.9 85.1 85.3 85.9 84.5 84.9 89.5 88.6 88.9 89.6 88.7 88.6 88.9
Table 3. Accuracy at different orders K
View tableTable 3. Accuracy at different orders K
K Mean class accuracy /% Overall accuracy /% 1 2 3 4 5 6 82.6 84.3 83.4 84.6 85.3 85.7 87.0 88.9 88.0 88.8 89.6 89.3
Table 4. mIoU values of segmentation on ShapeNet
View tableTable 4. mIoU values of segmentation on ShapeNet
Category Number of models Part mIoU /% Model in Ref. [17] SyncSpecCNN[ 18 ]PointNet[ 8 ]GraphPNet Airplane
Bag
Cap
Car
Chair
Earphone
Guitar
Knife
Lamp
Laptop
Motorbike
Mug
Pistol
Rocket
Skateboard
Table2690
76
55
898
3758
69
787
392
1547
451
202
184
283
66
152
52714
2
2
4
4
3
3
2
4
2
6
2
3
3
3
381.0
78.4
77.7
75.7
87.6
61.9
92.0
85.4
82.5
95.7
70.6
91.9
85.9
53.1
69.8
75.381.6
81.7
81.9
75.2
90.2
74.9
93.0
86.0
84.7
95.6
66.7
92.7
81.6
60.6
82.9
82.183.4
78.7
82.5
74.9
89.6
73.0
91.5
85.9
80.8
95.3
65.2
93.0
81.2
57.9
72.8
80.679.8
71.2
83.5
72.4
90.2
69.4
92.5
81.1
81.2
96.7
64.4
93.3
87.9
55.6
74.7
84.6
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Xiangdan Hou, Xixin Yu, Hongpu Liu. 3D Point Cloud Classification and Segmentation Model Based on Graph Convolutional Network[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181019
Paper Information
Category: Image Processing
Received: Jan. 2, 2020
Accepted: Feb. 24, 2020
Published Online: Sep. 2, 2020
The Author Email: Liu Hongpu (1367456185@qq.com)
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