<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The common point cloud registration algorithms are usually divided into initial registration and precise registration. In this paper, SAC-IA algorithm, which is commonly used in PCL, is selected for initial registration, and the traditional ICP algorithm is used for accurate registration. Three different feature descriptors (3D shape context, Point Feature Histograms, Fast Point Feature Histograms) are used to realize SAC-IA algorithm and ICP precise registration algorithm. During the implementation of the algorithm, the registration time and registration error of point cloud are calculated; according to the experimental results, the registration time and registration error of SAC-IA algorithm and ICP algorithm based on three different descriptors are compared. The results show that the registration algorithm based on 3D shape context has high accuracy, but the registration time is too long, which is not suitable for a large number of point cloud data; the registration algorithm based on fast point feature histograms has short registration time and good registration effect.</p></abstract>

The common point cloud registration algorithms are usually divided into initial registration and precise registration. In this paper, SAC-IA algorithm, which is commonly used in PCL, is selected for initial registration, and the traditional ICP algorithm is used for accurate registration. Three different feature descriptors (3D shape context, Point Feature Histograms, Fast Point Feature Histograms) are used to realize SAC-IA algorithm and ICP precise registration algorithm. During the implementation of the algorithm, the registration time and registration error of point cloud are calculated; according to the experimental results, the registration time and registration error of SAC-IA algorithm and ICP algorithm based on three different descriptors are compared. The results show that the registration algorithm based on 3D shape context has high accuracy, but the registration time is too long, which is not suitable for a large number of point cloud data; the registration algorithm based on fast point feature histograms has short registration time and good registration effect.

Comparison of Several Different Registration Algorithms

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Comparison of Several Different Registration Algorithms"}

The common point cloud registration algorithms are usually divided into initial registration and precise registration. In this paper, SAC-IA algorithm, which...

Comparison of registration algorithms	Feature Descriptors
Comparison of registration algorithms	3Dsc	PFH	FPFH
SAC-IA runtime	417.381 s	22.727 s	8.085 s
x-axis rotation error	0.0400952 °	0.0474209 °	0.0265896 °
y-axis rotation error	0.811471 °	0.758933 °	0.709945 °
z-axis rotation error	-0.740596 °	-0.734409 °	-0.756489 °
x-axis translation error	0.012691 mm	0.007121 mm	0.019262 mm
y-axis translation error	-0.297463 mm	-0.29991 mm	-0.298785 mm
z-axis translation error	-0.192225 mm	-0.194115mm	-0.194264 mm
distance error	0.354395 mm	0.357320 mm	0.356906 mm

Comparison of registration algorithms	Feature Descriptors
Comparison of registration algorithms	3Dsc	PFH	FPFH
total time	415.765 s	23.804 s	9.094 s
SAC-IA runtime	414.86 s	23.15 s	8.435 s
ICP runtime	0.905 s	0.654 s	0.659 s
x-axis rotation error	0.0141387 °	0.0325149 °	0.0134278 °
y-axis rotation error	0.764633 °	0.721214 °	0.744733 °
z-axis rotation error	-0.758194 °	-0.76543 °	-0.770207 °
x-axis translation error	0.0128116 mm	0.013648 mm	0.015574 mm
y-axis translation error	-0.298834 mm	-0.29914 mm	-0.299785 mm
z-axis translation error	-0.194931 mm	-0.19437 mm	-0.193715 mm
distance error	0.357021 mm	0.357004 mm	0.357266 mm

Comparison of Several Different Registration Algorithms

Publicado en línea: 23 feb 2022

Páginas: 22 - 27

DOI: https://doi.org/10.21307/ijanmc-2020-004

Palabras clave
Point Cloud Registration, SAC-IA Algorithm, ICP Algorithm, Registration Time, Registration Error

© 2020 Lulu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

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INITIAL REGISTRATION ERROR TABLE

ACCURATE REGISTRATION ERROR TABLE

Comparison of Several Different Registration Algorithms

Publicado en línea: 23 feb 2022

Páginas: 22 - 27

DOI: https://doi.org/10.21307/ijanmc-2020-004

Palabras clavePoint Cloud Registration, SAC-IA Algorithm, ICP Algorithm, Registration Time, Registration Error

© 2020 Lulu Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

INITIAL REGISTRATION ERROR TABLE

ACCURATE REGISTRATION ERROR TABLE

Palabras clave
Point Cloud Registration, SAC-IA Algorithm, ICP Algorithm, Registration Time, Registration Error