TY - JOUR
T1 - 3D shape modeling using a self-developed hand-held 3D laser scanner and an efficient HT-ICP point cloud registration algorithm
AU - Chen, Jia
AU - Wu, Xiaojun
AU - Yu Wang, Michael
AU - Li, Xuanfu
N1 - Funding Information:
This project is partially supported by Science and Technology Basic Research Projects of Shenzhen (No. JC200903120184A JC201005260161A , and JC201104210015A ), Science and Technology Foundation of Shenzhen Nanshan (No. 201002 ). We would like to thank the Stanford Computer Graphics Laboratory for the permission to use the bunny models and T. Weise for the permission to use the coati models. The first author would like to thank Chiping Chen from Massachusetts Institute of Technology (MIT) and Bingkun Li from Southern Medical University for their English proof-reading and valuable suggestions. We would also like to thank the anonymous reviewers for their valuable comments and suggestions.
PY - 2013/2
Y1 - 2013/2
N2 - Firstly, we develop a cost-efficient hand-held three-dimensional (3D) laser scanner for optical 3D laser scan data acquisition. Then, an automatic registration algorithm is used for 3D laser scanning based 3D shape modeling. Inspired by the use of twist to parameterize rigid motion in workpiece localization, we present the Hong-Tan based ICP (Iterative Closest Point) automatic registration algorithm (named HT-ICP) for partially overlapping point clouds. Using the point clouds from Stanford 3D Scanning Repository, we compare HT-ICP with the original ICP algorithm and its main variants, and experimental results show that the HT-ICP algorithm improves both the speed and accuracy of registration. Then we give the performance analysis with increasing amount of noise, and show the power of the 4PCSHT-ICP strategy for working directly on the raw noisy data. Furthermore, in the process of complete 3D shape modeling of Venus-head-statue, we demonstrate the effectiveness of the HT-ICP algorithm when aligning the actually acquired noisy point clouds from our self-developed low-precision hand-held scanner.
AB - Firstly, we develop a cost-efficient hand-held three-dimensional (3D) laser scanner for optical 3D laser scan data acquisition. Then, an automatic registration algorithm is used for 3D laser scanning based 3D shape modeling. Inspired by the use of twist to parameterize rigid motion in workpiece localization, we present the Hong-Tan based ICP (Iterative Closest Point) automatic registration algorithm (named HT-ICP) for partially overlapping point clouds. Using the point clouds from Stanford 3D Scanning Repository, we compare HT-ICP with the original ICP algorithm and its main variants, and experimental results show that the HT-ICP algorithm improves both the speed and accuracy of registration. Then we give the performance analysis with increasing amount of noise, and show the power of the 4PCSHT-ICP strategy for working directly on the raw noisy data. Furthermore, in the process of complete 3D shape modeling of Venus-head-statue, we demonstrate the effectiveness of the HT-ICP algorithm when aligning the actually acquired noisy point clouds from our self-developed low-precision hand-held scanner.
KW - 3D image processing
KW - 3D laser scanning system
KW - Point cloud registration
UR - http://www.scopus.com/inward/record.url?scp=84866510413&partnerID=8YFLogxK
U2 - 10.1016/j.optlastec.2012.06.015
DO - 10.1016/j.optlastec.2012.06.015
M3 - Article
AN - SCOPUS:84866510413
SN - 0030-3992
VL - 45
SP - 414
EP - 423
JO - Optics and Laser Technology
JF - Optics and Laser Technology
IS - 1
ER -