TY - JOUR
T1 - A robust method for multi-view 3D data stitching based on pasted marked points
AU - Luo, Hua
AU - Zhang, Ke
AU - Yang, Na
AU - Tan, Minghu
AU - Wang, Jingyu
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/3/31
Y1 - 2024/3/31
N2 - High-precision three-dimensional (3D) measurement techniques commonly perform 3D point cloud data stitching using pasted marked points. However, pasted marked points exhibit a high degree of randomness and are susceptible to mismatching due to their structural similarity. Therefore, this paper presents a robust method for multi-view 3D data stitching based on pasted marked points (RMSM). First, potential matched marked point pairs (MMPP) are identified according to spatial feature invariance constraints, and a matching strength calculation model is established to find the fiducial point pairs. Then, a quick public MMPP searching algorithm using the congruent triangle search method is proposed. Thus, the problem of mismatching caused by structurally similar marked points can be eliminated, and robust stitching of 3D data from different views can be achieved. In simulation and measurement experiments, the RMSM demonstrates superior accuracy compared to alternative methods and holds promise for application in various multi-view 3D data stitching methodologies.
AB - High-precision three-dimensional (3D) measurement techniques commonly perform 3D point cloud data stitching using pasted marked points. However, pasted marked points exhibit a high degree of randomness and are susceptible to mismatching due to their structural similarity. Therefore, this paper presents a robust method for multi-view 3D data stitching based on pasted marked points (RMSM). First, potential matched marked point pairs (MMPP) are identified according to spatial feature invariance constraints, and a matching strength calculation model is established to find the fiducial point pairs. Then, a quick public MMPP searching algorithm using the congruent triangle search method is proposed. Thus, the problem of mismatching caused by structurally similar marked points can be eliminated, and robust stitching of 3D data from different views can be achieved. In simulation and measurement experiments, the RMSM demonstrates superior accuracy compared to alternative methods and holds promise for application in various multi-view 3D data stitching methodologies.
KW - 3D point cloud data stitching
KW - Congruent triangles
KW - Matching strength
KW - Public marked points
UR - http://www.scopus.com/inward/record.url?scp=85186434474&partnerID=8YFLogxK
U2 - 10.1016/j.measurement.2024.114364
DO - 10.1016/j.measurement.2024.114364
M3 - 文章
AN - SCOPUS:85186434474
SN - 0263-2241
VL - 228
JO - Measurement: Journal of the International Measurement Confederation
JF - Measurement: Journal of the International Measurement Confederation
M1 - 114364
ER -