Acta Optica Sinica, Volume. 39, Issue 2, 0215002(2019)
Point Cloud Registration in Multidirectional Affine Transformation with Variance Compensation
Figures & Tables(17)
![Registration effects of point clouds after similarity transformation by different algorithms. (a) Algorithm in Ref. [4]; (b) ICP; (c) Scale-ICP; (d) CPD; (e) MARVC](/Images/icon/loading.gif){kind=icon}
Fig. 3. Registration effects of point clouds after similarity transformation by different algorithms. (a) Algorithm in Ref. [4]; (b) ICP; (c) Scale-ICP; (d) CPD; (e) MARVC
Fig. 4. Initial states after multidirectional affine transformation. (a) Bunny; (b) Horse
Fig. 5. Registration effects for different algorithms after multidirectional affine transformation. (a) Algorithm in Ref. [4]; (b) ICP; (c) Scale-ICP; (d) CPD; (e) MARVC
Fig. 6. Registration effects of point clouds for different algorithms under random loss and multi-directional affine transformation. (a) Scale-ICP; (b) CPD; (c) MARVC
Fig. 7. Registration effects of point clouds with 20 dB random noise for different algorithms under random loss and multi-directional affine transformation. (a) ICP; (b) Scale-ICP; (c) CPD; (d) MARVC
Fig. 8. Actual objects scanned by portable laser scanner, obtained data, and registration effects. (a) Three groups of objects; (b) obtained data; (c) registration effects by MARVC algorithm
Table 1. RMSE for different algorithms mm
View tableTable 1. RMSE for different algorithms mm
Point cloud s Algorithm in Ref. [4] ICP Scale-ICP CPD MARVC 1.5 1.8562 1.8216 0.7687 0.3727 5.6550×10-4 Bunny 2 3.2229 3.1774 0.0013 0.2641 3.6760×10-4 3 6.7786 6.7907 2.1157 0.3519 3.1740×10-4 1.5 12.3420 13.0710 7.0815 2.2140 7.9900×10-4 Horse 2 29.2730 37.7740 5.1928 3.1270 8.0440×10-4 3 63.0870 62.2310 6.4387 3.0251 2.2180×10-3
Table 2. Registration time for different algorithmss
View tableTable 2. Registration time for different algorithmss
Point cloud s Algorithm in Ref. [4] ICP Scale-ICP CPD MARVC 1.5 6.2565 649.6780 8.1354 988.3850 2.7407 Bunny 2 5.9417 351.4250 21.6884 952.2650 4.1969 3 6.5417 257.1220 8.4478 986.4610 3.5356 1.5 7.1232 296.7850 9.1698 2146.4000 4.6706 Horse 2 6.8912 499.6830 24.2360 2241.3700 0.4924 3 7.2567 423.3320 14.3790 2549.5600 1.3736
Table 3. RMSE for different algorithmsmm
View tableTable 3. RMSE for different algorithmsmm
Point cloud Algorithm in Ref. [4] ICP Scale-ICP CPD MARVC Bunny 14.5430 9.2450 3.6550 0.1160 1.1030×10-3 Horse 39.3240 38.8230 10.9120 107.4520 3.1610×10-3
Table 4. Registration time for different algorithmss
View tableTable 4. Registration time for different algorithmss
Point cloud Algorithm in Ref. [4] ICP Scale-ICP CPD MARVC Bunny 2.3290 1187.5130 24.3850 208.6340 2.8120 Horse 3.3590 502.6340 27.3530 434.2230 0.8770
Table 5. RMSE for different algorithms after random loss of data pointsmm
View tableTable 5. RMSE for different algorithms after random loss of data pointsmm
Point cloud ICP Scale-ICP CPD MARVC Bunny 8.0910 8.0910 0.3080 0.0302 Horse 38.8170 11.3050 2.1010 0.0763
Table 6. Registration time for different algorithms after random loss of data pointss
View tableTable 6. Registration time for different algorithms after random loss of data pointss
Point cloud ICP Scale-ICP CPD MARVC Bunny 949.7260 31.7890 191.8430 1.3710 Horse 420.9660 103.7960 363.9730 3.2760
Table 7. RMSE for different algorithms under different interference environmentsmm
View tableTable 7. RMSE for different algorithms under different interference environmentsmm
Proportion of lost points 10% 20% Signal-to-noise ratio 15 dB 20 dB 25 dB 15 dB 20 dB 25 dB ICP 0.9852 0.9460 0.9371 0.9886 0.9808 1.005 Bunny Scale-ICP 1.4010 1.5680 1.6530 1.5020 1.6020 1.6670 CPD 0.4449 0.2958 0.3768 0.3990 0.3561 0.3141 MARVC 0.3976 0.2366 0.1414 0.3952 0.2398 0.2104 ICP 5.5390 5.2670 5.1220 23.3880 9.7710 9.2740 Horse Scale-ICP 6.1890 4.8690 9.4320 18.5440 9.5680 9.1640 CPD 5.7380 4.5980 3.2550 5.4770 3.4740 3.5850 MARVC 4.6890 3.2150 2.1490 4.7420 2.6170 2.1290
Table 8. Registration time for different algorithms under different interference environmentss
View tableTable 8. Registration time for different algorithms under different interference environmentss
Proportion of lost points 10% 20% Signal-to-noise ratio 15 dB 20 dB 25 dB 15 dB 20 dB 25 dB ICP 1023.0880 918.7300 914.6390 830.3700 779.6490 846.3800 Bunny Scale-ICP 31.0410 20.2570 17.1920 31.8360 17.3670 17.8140 CPD 182.9190 204.9210 210.1450 170.3430 170.8650 171.7440 MARVC 3.4680 3.3600 4.3160 4.1900 7.5390 4.8620 ICP 470.2290 428.7340 510.2460 747.7910 232.7110 412.3490 Horse Scale-ICP 45.0120 35.2130 84.9230 56.1270 44.2320 62.5230 CPD 397.9310 492.1960 716.1470 405.0180 402.9340 297.3500 MARVC 1.8410 1.7860 1.7430 1.4060 2.4450 1.5570
Table 9. Registration effects of three groups of objects for different algorithms
View tableTable 9. Registration effects of three groups of objects for different algorithms
Object No. Parameter MARVC ICP Scale-ICP CPD Object 1 RMSE /mm 0.5974 2.4375 3.8148 0.7934 Time /s 5.773 634.755 6.608 64.099 Object 2 RMSE /mm 0.5724 7.4200 7.4088 3.1088 Time /s 4.835 446.558 4.632 47.154 Object 3 RMSE /mm 0.6431 8.9753 9.4262 0.6919 Time /s 6.703 827.352 16.724 242.237
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Chang Wang, Qin Shu, Yunxiu Yang, Shijie Deng. Point Cloud Registration in Multidirectional Affine Transformation with Variance Compensation[J]. Acta Optica Sinica, 2019, 39(2): 0215002
Paper Information
Category: Machine Vision
Received: Jun. 25, 2018
Accepted: Sep. 29, 2018
Published Online: May. 10, 2019
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