测绘通报 ›› 2025, Vol. 0 ›› Issue (6): 62-67.doi: 10.13474/j.cnki.11-2246.2025.0611

• 学术研究 • 上一篇    

融合多源多视角数据的真彩三维重建技术

张莉君1,2, 高云涵1,2, 邹小凡1,2, 史航1,2, 解杨敏1,2   

  1. 1. 上海大学机电工程与自动化学院, 上海 200444;
    2. 上海大学上海市智能制造及机器人重点实验室, 上海 200444
  • 收稿日期:2024-11-19 发布日期:2025-07-04
  • 通讯作者: 解杨敏。E-mail:xieym@shu.edu.cn
  • 作者简介:张莉君(1999—),女,硕士,主要研究方向为点云匹配、三维重建、回环检测等。E-mail:junjun91026@163.com
  • 基金资助:
    上海市自然科学基金(20ZR1419100)

Colorized 3D reconstruction technology integrating multi-source and multi-view data

ZHANG Lijun1,2, GAO Yunhan1,2, ZOU Xiaofan1,2, SHI Hang1,2, XIE Yangmin1,2   

  1. 1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China;
    2. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200444, China
  • Received:2024-11-19 Published:2025-07-04

摘要: 随着数字化需求日益增长,单一传感器数据已经难以完成复杂建模任务,且单视角容易存在数据稀疏或遮挡问题。针对该问题,本文提出了两套三维重建系统,搭载激光雷达、单目相机及IMU等多传感器,分别应用于室内、室外多视角数据采集。另外,本文还提出了一种融合多源多视角数据的真彩三维重建技术。首先通过联合标定获取各传感器之间的坐标系转换关系;然后利用视觉惯性耦合系统进行运动估计,以获取准确姿态和轨迹,基于此对单视角激光点云进行去畸变优化及真彩赋色;最后基于色彩几何混合信息进行多视角点云拼接,获取扫描对象的真彩三维模型,在室内室外场景下进行了测试验证。试验结果表明,本文方法三维重建精度高于先进算法,建模误差能达到厘米级,且算法稳健性更高。

关键词: 多源感知, 多视角点云匹配, 三维重建系统, 真彩三维重建

Abstract: With the growing demands of digitalization, data acquired from a single sensor has become inadequate for complex modeling tasks, and single-view approaches are inherently prone to data sparsity and occlusion issues. To address this problem, this paper proposes two sets of 3D reconstruction systems, which are equipped with multiple sensors including LiDAR, monocular cameras, and IMU, and can be respectively applied to multi-view data collection in both indoor and outdoor environments. Furthermore, this paper also presents a colorized 3D reconstruction technology based on the fusion of multi-source and multi-view data. The prerequisite is to obtain the coordinate system transformation relationships among various sensors through joint calibration. Then, the visual-inertial coupling system is utilized for motion estimation to acquire accurate postures and trajectories. Based on this, the single-view laser point clouds are optimized for distortion removal and assigned with true colors. Finally, multi-view point cloud stitching is carried out based on the mixed information of color and geometry to obtain the true-color 3D model of the scanned object. Tests and verifications have been conducted in both indoor and outdoor scenarios. The experimental results show that the 3D reconstruction accuracy of this method is higher than that of advanced algorithms, with the modeling error reaching the centimeter level. Additionally, the algorithm has higher robustness.

Key words: multi-source perception, multi-view point cloud matching, 3D reconstruction system, colorized 3D reconstruction

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