Indoor automatic 3D modeling technology integrating handheld SLAM LiDAR and image data

doi:10.13474/j.cnki.11-2246.2026.0529

Abstract

Abstract: [Purposes] To address the dual requirements of high-precision geometry and realistic textures for indoor 3D modeling,as well as the limitations of single data sources and the inefficiency of traditional registration methods,this paper proposes an efficient,robust,and highly automated indoor 3D modeling technology.[Methods] A handheld laser SLAM scanner integrated with a camera is used to simultaneously collect high-precision point clouds and texture images.Initial POS data are derived from factory calibration parameters.An improved point cloud-image registration algorithm combining geometric constraints and feature matching is proposed to achieve high-precision data fusion.Subsequently,3D reconstruction is accomplished through point-cloud-driven geometric modeling and optimized texture mapping.[Findings] Experimental results indicate that the geometric error of the 3D model is less than 2 cm,with realistic textures.The entire process takes 58.5 min,significantly outperforming traditional manual modeling methods.[Conclusions] This technology leverages the complementary strengths of LiDAR point clouds and image data,reduces sensitivity to lighting conditions,improves modeling efficiency and automation,and provides a reliable technical solution for indoor realistic 3D reconstruction.

Key words: indoor realistic 3D model, automatic 3D reconstruction, point cloud-image registration, handheld laser SLAM, fusion modeling

CLC Number:

P237

ZHANG Shijie, MIAO Peipei, XU Linjie, GAO Yunlong, PENG Fangyuan, LI Chunnan, SUN Xinhao. Indoor automatic 3D modeling technology integrating handheld SLAM LiDAR and image data[J]. Bulletin of Surveying and Mapping, 2026, 0(5): 179-184.

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