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1 Image-Based Image-Based Example Acquistion Setup Example - PDF document

Sep 29, 2023 •234 likes •291 views

Homogeneous BRDF Homogeneous BRDF Realistic Materials Realistic Materials BRDF Measurement Spatially Varying BRDF Spatially Varying BRDF Approaches - Sampling Approaches - Sampling dense sampling for each texel Reflectance Fields,

  1. Homogeneous BRDF Homogeneous BRDF Realistic Materials Realistic Materials BRDF Measurement Spatially Varying BRDF Spatially Varying BRDF Approaches - Sampling Approaches - Sampling • dense sampling for each texel – Reflectance Fields, BTF • sparse sampling • sparse sampling – image-based BRDF Measurement – combining samples from different surface points • spatial variation – constant specular part vs. clustered BRDFs Approaches - Illumination Approaches - Illumination BRDF Measurement BRDF Measurement • point light • Gonioreflectometer – controlled condition sensor sensor – interreflections most often neglected interreflections most often neglected light source light source • environment maps – still direct illumination only • global inverse illumination sample sample 1

  2. Image-Based Image-Based Example Acquistion Setup Example Acquistion Setup BRDF Measurement BRDF Measurement • [Marschner 1999, • The following demonstrates and image- camera camera Lu & Koenderink 1998, spaced acquisition setup [Lensch 2002,2003] …] • There are other possible variants • There are other possible variants – capture lots of BRDF samples at one shot by a sensor array / camera. – homogeneous, isotropic materials only curved sample curved sample Acquisition Setup Acquisition Setup BRDF Fitting BRDF Fitting – Camera and light source are moved manually around Registration Registration View View BRDF BRDF the object. the object Resampling Resampling Resampling Resampling Vi ibilit / Vi ibilit / Visibility/ Visibility/ Acquisition Acquisition Fitting Fitting Shadows Shadows – Positions are calibrated with respect to the object. – The dark room reduces reflections from the environment. BRDF Acquisition BRDF Acquisition 3D-2D Registration 3D-2D Registration – Capture HDR-images from various viewpoints with different light source positions. – calibrated gantry – corresponding points corresponding points – silhouette-based method 2

  3. Light Source Position Light Source Position Light Source Position Light Source Position – detect highlights of ring flash reflections – detect highlights of light source reflections – determine the position of the spheres – reconstruct light source position r d d d d Light Source Position Light Source Position Resampling Resampling r x – for each point on the surface: find all images where the point is visible and lit take sample at corresponding pixel position Resampling Resampling BRDF Fitting BRDF Fitting • Now at every location on the object: – Have several samples Registration Registration View View BRDF BRDF • For different view/light combinations For different view/light combinations Resampling Resampling Resampling Resampling Vi ibilit / Vi ibilit / Visibility/ Visibility/ Acquisition Acquisition Fitting Fitting Shadows Shadows • Number depends on number of images! – Using these samples, fit a BRDF now 3

  4. Fitting a BRDF to the data Fitting a BRDF to the data Results Results • Fitting a separate BRDF at every texel – Choose a BRDF model (say Cook-Torrance) – BRDF model has several free parameters BRDF model has several “free” parameters – Perform non-linear fitting (Levenberg-Marquart for instance) of model to measured data • Can be done in Matlab – Yields parameters per pixel Results Results Results Results Results Results 4

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