Abstract
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.
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