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HUANG Hui-ming, LIU Gui-hua, DENG Lei, SONG Tao, QIN Fu-ping. Multi-line laser 3D reconstruction based on geometric estimation optimization[J]. Chinese Optics. doi: 10.37188/CO.2024-0184
Citation: HUANG Hui-ming, LIU Gui-hua, DENG Lei, SONG Tao, QIN Fu-ping. Multi-line laser 3D reconstruction based on geometric estimation optimization[J]. Chinese Optics. doi: 10.37188/CO.2024-0184

Multi-line laser 3D reconstruction based on geometric estimation optimization

cstr: 32171.14.CO.2024-0184
Funds:  Supported by National Natural Science Foundation of China (No. 11602292), and the projects of Guangzhou power supply bureau of Guangdong Power Grid Co., Ltd (No. 080044KK52190002)
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  • Corresponding author: liughua_swit@163.com
  • Received Date: 08 Oct 2024
  • Accepted Date: 22 Nov 2024
  • Available Online: 05 Dec 2024
  • In traditional multi-line laser 3D reconstruction technology, researchers typically use a method that combines binocular epipolar constraints with laser spatial equations. This method first utilizes epipolar constraints to identify multiple potential matching points, and then filters out the correct matching points through the spatial equations of the multi-line laser. The process of 3D reconstruction is then achieved using these matching points. However, due to the inevitable noise affecting the multi-line laser lines, the extracted laser center coordinates often contain certain errors. These errors can lead to the inability to obtain high-precision 3D data when using matching points found based on epipolar constraints for 3D reconstruction directly. To address this issue, this paper proposes a method based on geometric estimation to achieve 3D reconstruction of multi-line lasers. First, by calibrating the quadratic surface equations of the multi-line laser, combined with the binocular epipolar constraint method, the initial matching points of the multi-line laser can be calculated. After finding the correct initial matching points, a geometric distance minimization estimation model is established using the distance constraint from points to epipolar lines. This geometric distance refers to the distance from the laser center points in the left and right images to their corresponding epipolar lines. Through this geometric distance minimization optimization estimation, new matching points that better conform to the epipolar constraints can be recalculated. Finally, these new matching points are used to complete the 3D reconstruction of the multi-line laser. Compared to the traditional method based on epipolar constraints, the algorithm proposed in this paper performs better in terms of matching and accuracy.The accuracy of the final 3D reconstruction can reach about 0.02mm. With this method, the overall accuracy of binocular multi-line laser reconstruction can be significantly improved, thereby obtaining more accurate and reliable 3D data.

     

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