Automatic and accurate full-view registration method for 3D scanning system

Pei Xu; Feifei Gu; Zhan Song; Juan Zhao; Jun Li

doi:10.1117/12.2525655

21 June 2019 Automatic and accurate full-view registration method for 3D scanning system

Pei Xu, Feifei Gu, Zhan Song, Juan Zhao, Jun Li

Proceedings Volume 11056, Optical Measurement Systems for Industrial Inspection XI; 110563M (2019) https://doi.org/10.1117/12.2525655
Event: SPIE Optical Metrology, 2019, Munich, Germany

Abstract

In a structured light-based 3D scanning system, the overall 3D information of to-be-measured objects cannot be retrieved at one time automatically. Currently the 3D registration algorithms can be divided into the auxiliary objects-based method and the feature points-based method. The former requires extra calibration objects or positioning platforms, which limits its application in free-form 3D scanning task. The latter can be conducted automatically, however, most of them tried to recover the motion matrix from extracted 2D features, which has been proved to be inaccurate. This paper proposed an automatic and accurate full-view registration method for 3D scanning system. Instead of using the 3D information of detected feature points to estimate the coarse motion matrix, 3D points reconstructed by the 3D scanning system were utilized. Firstly, robust SIFT features were extracted from each image and corresponding matching point pairs are achieved from two adjacent left images. Secondly, re-project all of the 3D point clouds onto the image plane of each left camera and corresponding 2D image points can be obtained. Filter out correct matching points from all 2D reprojection points under the guidance of the extracted SIFT matching points. Then, the covariance method was adopted to estimate the coarse registration matrix of adjacent positions. This procedure was repeated among every adjacent viewing position of the 3D scanning system. Lastly, fast ICP algorithm was performed to conduct fine registration of multi-view point clouds. Experiments conducted on real data have verified the effectiveness and accuracy of the proposed method.

Citation Download Citation

Pei Xu, Feifei Gu, Zhan Song, Juan Zhao, and Jun Li "Automatic and accurate full-view registration method for 3D scanning system", Proc. SPIE 11056, Optical Measurement Systems for Industrial Inspection XI, 110563M (21 June 2019); https://doi.org/10.1117/12.2525655

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KEYWORDS

Clouds

3D scanning

Structured light

3D image processing

Cameras

Image registration

3D modeling

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