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Novel calibration procedure for SVBRDF estimation of 3D objects using directional illumination and structured light projection

机译:使用定向照明和结构化光投影对3D对象进行SVBRDF估计的新型校准程序

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摘要

Estimation of geometry and reflectance of 3D objects requires that surface geometry is registered together with photometric data. We present a method which combines geometrical camera calibration and photometric calibration into a single procedure utilizing only one calibration target. Using structured light projection and directional illumination, the surface of a 3D object can be registered with an integrated measuring device. To estimate spatial distribution of reflectance parameters, a Spatially Varying Bidirectional Reflectance Distribution Function (SVBRDF) model is used. We also show a 3D image processing method to estimate SVBRDF parameters using an arbitrary defined array of illuminators and algorithms to reconstruct this surface using specialized visualization software. This approach allows for effective measurement of geometry and visual properties of 3D objects represented by a dense point cloud model. It can become a valuable tool for documentation of digital heritage and in industrial computer vision applications.
机译:估计3D对象的几何形状和反射率要求将表面几何形状与光度数据一起注册。我们提出了一种仅使用一个校准目标就将几何相机校准和光度学校准合并为单个过程的方法。使用结构化的光投影和定向照明,可以将3D对象的表面与集成的测量设备对齐。为了估计反射率参数的空间分布,使用了空间变化的双向反射率分布函数(SVBRDF)模型。我们还展示了一种3D图像处理方法,可使用任意定义的照明器阵列估算SVBRDF参数,并使用专用的可视化软件重建该表面的算法。这种方法可以有效测量由密集点云模型表示的3D对象的几何形状和视觉特性。它可以成为记录数字遗产和工业计算机视觉应用中的宝贵工具。

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