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用于移动测绘的全景图像与激光雷达点云的基于线的配准

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

作者信息

Cui Tingting, Ji Shunping, Shan Jie, Gong Jianya, Liu Kejian

机构信息

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.

Research Center of Remote Sensing in Public Security, People's Public Security University of China, Beijing 100038, China.

出版信息

Sensors (Basel). 2016 Dec 31;17(1):70. doi: 10.3390/s17010070.

Abstract

For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

摘要

对于多传感器集成系统,如移动测绘系统(MMS),传感器级别的数据融合,即光学相机与激光雷达之间的二维到三维配准,是进行更高级别融合及进一步应用的前提条件。本文提出了一种针对移动测绘系统采集的全景图像和激光雷达点云的基于直线的配准方法。我们首先介绍系统配置和规格,包括移动测绘系统、三维激光雷达扫描仪以及两种全景相机模型的坐标系。然后我们为全景相机建立基于直线的变换模型。最后,通过视觉检查和定量比较对所提出的配准方法针对两种相机模型进行评估。结果表明,基于直线的配准方法在理想球面或严格全景相机模型下都能显著改善全景图像与激光雷达数据集的对齐效果,其中后者更可靠。

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