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3D reconstruction methods compared for road roughness analysis

By PulseAugur Editorial · [1 sources] ·

A new research paper evaluates four 3D reconstruction methods—COLMAP, Meshroom, Metashape, and 3D Gaussian Splatting (3DGS)—for their effectiveness in analyzing road surface roughness using smartphone imagery. The study found that COLMAP was most sensitive to micro-textures, while Meshroom offered balanced reconstructions. Metashape produced smoother geometry due to internal filtering, and 3DGS captured irregularities but with higher noise and lower density. The findings suggest that open-source reconstruction pipelines are practical for relative roughness evaluation in low-cost pavement monitoring. AI

RANK_REASON This is a research paper evaluating different methods for a specific technical task. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

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3D reconstruction methods compared for road roughness analysis

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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Marouane Elmegdar, Teng Xiao ·

    Comparative evaluation of photogrammetric reconstruction methods and 3D Gaussian Splatting for road surface roughness analysis

    arXiv:2605.29452v1 Announce Type: new Abstract: Image-based 3D reconstruction offers a low-cost alternative to traditional sensor-based techniques for road surface assessment. This study compares four reconstruction pipelines--COLMAP, Meshroom, Metashape, and 3D Gaussian Splattin…

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