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16 October 2019 Full-surface 3-D reconstruction based on surround structured lighting
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Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019); 1120527 (2019) https://doi.org/10.1117/12.2548032
Event: Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 2019, Phuket, Thailand
Abstract
In a conventional fringe projection profilometry (FPP) consisted of a camera and a projector, just one-sided 3D data of the tested object can be obtained by a single-shot measurement. Therefore, tools such as turntables are commonly used to obtain 360-degree 3D point cloud data of objects. However, this method requires multiple measurements and point cloud registration, which is time consuming and laborious. With the help of two planar mirrors, this paper proposes an improved system that captures fringe images from three different perspectives including one real camera and two virtual cameras. The information of the planar mirrors (i.e., the mirror calibration) is achieved by artificially attaching the featured pattern to the surface of the mirrors. Using the calibration parameters of the planar mirrors, the 3D point cloud data obtained by the virtual cameras can be converted into the real coordinate system, thereby reconstructing the full-surface 3D point cloud data with relative roughness. Finally, an improved ICP algorithm is introduced to obtain high-precision 360-degree point cloud data. The experimental results demonstrate that with the help of the mirrors, our system can obtain high-quality full-surface 360-degree profile results of the measured object at high speed.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hao Xu, Wei Yin, Chen Yang, Jiachao Li, Shijie Feng, Tianyang Tao, Qian Chen, and Chao Zuo "Full-surface 3-D reconstruction based on surround structured lighting", Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 1120527 (16 October 2019); https://doi.org/10.1117/12.2548032
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