From Global Illumination To Inverse Global Illumination. Yizhou Yu Computer Science Division University of California at Berkeley. Publications. http://www.cs.berkeley.edu/~yyz. - PowerPoint PPT Presentation
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Ongoing Work: Recovering Photometric PropertiesYizhou Yu Publications Y. Yu and H. Wu, A Rendering Equation for Specular Transfers and Its Integration into Global Illumination, Eurographics’97 P. Debevec, Y. Yu and G. Borshukov, Efficient View-Dependent Image-Based Rendering with Projective Texture-Mapping, Eurographics Workshop on Rendering’98 Y. Yu and J. Malik, Recovering Photometric Properties of Architectural Scenes from Photographs, Siggraph’98 Y. Yu, P. Debevec, J. Malik and T. Hawkins, Inverse Global Illumination: Recovering Reflectance Models of Real Scenes from Photographs, Siggraph’99 http://www.cs.berkeley.edu/~yyz Yizhou Yu Vision A polygonal mesh and/or a set of curved surface patches Yizhou Yu Light Sources Yizhou Yu Light Transport Yizhou Yu With a mirror Without the mirror to calculate illumination from area sources via curved ideal specular reflectors. The physics of light transport has been well understood. In the absence of real-world geometry and reflectance, rendered images still look synthetic. Solution: Image-based Modeling and Rendering (IBMR) Yizhou Yu Recover geometry ( explicit or implicit ) Acquire texture maps Yizhou Yu Yizhou Yu Synthetic Renderings Yizhou Yu Yizhou Yu The Problem Need to factorize images into lighting and reflectance maps Illumination Radiance Reflectance Recover geometry Yizhou Yu 1st Generation IBMR Simplified Situation: Isolated Objects Simplified Situation: Isolated Objects VDTM was originally from Façade [ Debevec, Taylor & Malik, Siggraph’96]. Software implementation 20 frames per second on SGI RealityEngine 60 frames per second on SGI Onyx2 InfiniteReality Yizhou Yu Yizhou Yu Simplified Situation: Isolated Objects [ Ward 92 ], [Dana, Ginneken, Nayar & Koenderink 97] Isolated Objects under Direct Illumination [ Sato, Wheeler & Ikeuchi 97 ] General case of multiple objects under mutual illumination has not been studied. Yizhou Yu Re-render the scene Synthesized Images of the Room under Original and Novel Lighting Yizhou Yu IGI Outline IGI for general surfaces Computing diffuse albedo maps Bi, Bj, Ei measured using HDR photographs Fij known because geometry is known Solve for diffuse albedo Specular Kernel Ki as in [ Ward 92 ] N H Isotropic Kernel Anisotropic Kernel Recovering Diffuse and Specular Reflectance under Mutual Illumination Specular component of LPiAj is not known. ( unlike diffuse case, where LPiAj = LCkAj ) Cv Ck Aj Pi LPiAj LCkAj LCvPi Initialize Repeat Update and Yizhou Yu Estimation of S Estimate specular component of by ray-tracing using current guess of reflectance parameters. Similarly for Cv Ck Aj Pi LPiAj LCkAj LCvPi LPiAj LCkAj Detect specular highlight blobs on the surfaces. Choose a set of sample points inside and around each highlight area. Build hierarchical links between sample points and facets in the environment and use ray tracing to detect occlusion. Assign to each facet one photograph and one average radiance value captured at the camera position. Assign zero to Delta_S at each hierarchical link. For iter = 1 to n For each hierarchical link, use its Delta_S to update its radiance value. For each surface having highlight areas, optimize its BRDF parameters. For each hierarchical link, estimate its Delta_S with the new BRDF parameters. End Recovering Diffuse Albedo Maps Estimate specular component at each pixel from the recovered BRDF parameters using Monte Carlo ray-tracing. Subtract specular component to get the diffuse component of radiance, Ld(x). Gather irradiance, Ir(x), using Form-Factors over each surface. Combine from multiple photographs by robust weighted average. 111.unknown 112.unknown Diffuse Albedo Yizhou Yu Specular Roughness Yizhou Yu Yizhou Yu Diffuse Albedo Maps of Identical Posters in Different Parts of the Room Yizhou Yu Yizhou Yu A digital camera is the only data acquisition equipment used. Adopt an iterative procedure to obtain radiance distributions from specular surfaces. Exploit spatial coherence to recover specular reflectance models from one single photograph. Make use of multiple photographs to recover high-resolution diffuse albedo maps. Yizhou Yu Simplified Situation: Isolated Objects The sky The surrounding environment May contribute more light than the sky on shaded side. Modeled as a set of oriented Lambertian facets. Yizhou Yu R,G,B channels Project pixels into regions and obtain the average radiance Yizhou Yu Predicting Novel Illumination from the Environment Use photometric stereo to recover a Lambertian facet model for each region Synthetic Real 1156.unknown 1157.unknown 1158.unknown 1159.unknown 1160.unknown 1161.unknown Yizhou Yu Acknowledgments This is joint work with Jitendra Malik, Paul Debevec, George Borshukov, Tim Hawkins, C.J. Taylor and Hong Wu. Supported by ONR BMDO, the California MICRO program, Philips Corporation, Interval Research Corporation and Microsoft Graduate Fellowship. Yizhou Yu Publications Y. Yu and H. Wu, A Rendering Equation for Specular Transfers and Its Integration into Global Illumination, Eurographics’97 P. Debevec, Y. Yu and G. Borshukov, Efficient View-Dependent Image-Based Rendering with Projective Texture-Mapping, Eurographics Workshop on Rendering’98 Y. Yu and J. Malik, Recovering Photometric Properties of Architectural Scenes from Photographs, Siggraph’98 Y. Yu, P. Debevec, J. Malik and T. Hawkins, Inverse Global Illumination: Recovering Reflectance Models of Real Scenes from Photographs, Siggraph’99 http://www.cs.berkeley.edu/~yyz Yizhou Yu Yizhou Yu Optimization Technique Anisotropic Kernel ( Simplex Search ) set of points and then linearly interpolated. Yizhou Yu Take photographs for parts of the sky Use Levenberg-Marquardt algorithm to fit data sun zenith based on [Perez 93] Recover a distinct model for each environment region Obtain environment radiance maps. Set up over-determined systems as in photometric stereo and ignore inter-reflections. Solve for Render polygons using their identifiers as their colors Retrieve occluding polygons’ ids from color buffer Object-space shallow clipping to generate fewer polygons Yizhou Yu Pixel brightness value is a nonlinear function of radiance. Debevec & Malik[Siggraph’97] give a method to recover this nonlinear mapping. Radiance Radiance Intensity Saturation
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