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轮轨姿态反映着列车运行中轮与轨的接触关系,掌握高铁轮轨姿态是保障高铁安全运营的基础。基于计算机视觉技术的无接触方法可以通过采集运营状态下的轮轨图像,通过三维重建获取轮轨实时姿态。由于高铁运行速度快,轮轨表面光滑,给基于特征点提取的三维重建 (3D Reconstruction) 带来了极大挑战。本项目采用基于空间编码(Space Codification)的编码结构光(coded structured light)的方法,将单幅编码图案(one-shot)投影在轮轨表面,提高特征点的提取和识别精度,并将 De Bruijn 分析与小波变换(wavelet transform)分析相结合,增加了基于特征点的点云提取稠密度,从而实现了单次投影的点云稠密重建。项目完成了从半径95mm的球体提取17W条以上的点云 (Point Cloud) 数据,半径误差0.678mm,实现了对铁轨等多个物体的三维重建,完成了结构光三维重建软件开发,提供了基于主动视觉的三维重建和点云数据可视化展示、编辑的平台。

Home Page: https://tang5618.com/wordpress/?p=598

License: Apache License 2.0

C++ 81.22% C 7.12% C# 2.00% Visual Basic .NET 0.11% Batchfile 0.03% CMake 2.11% Cuda 0.49% Shell 0.04% HTML 0.53% CSS 0.01% JavaScript 0.41% TeX 0.26% Python 2.75% Java 2.41% Perl 0.03% Objective-C 0.04% Objective-C++ 0.39% Prolog 0.01% Dockerfile 0.01% PowerShell 0.03%

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