3D reconstruction method based on multi-view infrared sensor

SONG Li-mei; ZHANG Ji-peng; LI Yun-peng; LIU Zhen-ning; LUO Jing

doi:10.37188/CJLCD.2023-0026

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3D reconstruction method based on multi-view infrared sensor

Intelligent Imaging | 更新时间：2023-06-12

- 3D reconstruction method based on multi-view infrared sensor
- Chinese Journal of Liquid Crystals and Displays Vol. 38, Issue 6, Pages: 759-769(2023)
- 作者机构：
  
  1.天津工业大学天津市电气装备智能控制重点实验室，天津 300387
- 作者简介：
- 基金信息：
  
  Program for Innovative Research Team in University of Tianjin(TD13-5036);Tianjin Science and Technology Popularization Project(22KPXMRC00090)
- DOI：10.37188/CJLCD.2023-0026
  CLC：
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SONG Li-mei, ZHANG Ji-peng, LI Yun-peng, et al. 3D reconstruction method based on multi-view infrared sensor. [J]. Chinese Journal of Liquid Crystals and Displays 38(6):759-769(2023)
DOI：

SONG Li-mei, ZHANG Ji-peng, LI Yun-peng, et al. 3D reconstruction method based on multi-view infrared sensor. [J]. Chinese Journal of Liquid Crystals and Displays 38(6):759-769(2023) DOI： 10.37188/CJLCD.2023-0026.

摘要

为了实现有特征物体和无特征物体更精准的三维重建，本文研究了多视角传感器下三维点云的自动拼接算法。首先由不同视角的传感器双目标定后进行轴线数据的标定，接着在三维空间内对多条轴线数据进行分析并提出了一种基于多视角传感器轴线融合的点云拼接方法，从而计算出误差最小的最优轴线数据，最后以拟合出的轴线数据为轴心在世界坐标系内进行三维点云的拼接。实验结果表明，在1.3~1.9 m的测量范围内，本文所提出的拼接方法对直径为144.954 2 mm的标准球进行三维重建的误差在0.037 mm以内，重建无特征点物体和有特征点物体都能有较好的拼接效果且拼接时间不受点云总量大小的限制。该拼接方法基本满足三维重建的稳定性好、效率快、精度高等要求。

Abstract

In order to realize more accurate 3D reconstruction of featureless and featureless objects， this paper studies the automatic splicing algorithm of 3D point cloud under multi-view sensor. Firstly， the axis data was calibrated by the binocular calibration of sensors from different perspectives， and then multiple axis data were analyzed in three-dimensional space. A point cloud splicing method based on the axis fusion of sensors from multiple perspectives was proposed， so as to calculate the optimal axis data with the minimum error. Finally， the fitted axis data was used as the axis center to splice the three-dimensional point cloud in the world coordinate system. The experimental results show that the error of the proposed method is less than 0.037 mm in the measurement range of 1.3~1.9 m for the standard ball with a diameter of 144.954 2 mm， and the reconstruction of objects without and with feature points can have a good stitching effect， and the stitching time is not limited by the size of the total point cloud. This method basically meets the requirements of good stability， fast efficiency and high precision of 3D reconstruction.

关键词

三维重建点云拼接轴线

Keywords

three-dimensional reconstructionpoint cloud splicingaxis

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