“Inverse global illumination: recovering reflectance models of real scenes from photographs” by Yu, Debevec, Malik and Hawkins

  • ©Yizhou Yu, Paul E. Debevec, Jitendra Malik, and Tim Hawkins




    Inverse global illumination: recovering reflectance models of real scenes from photographs



    In this paper we present a method for recovering the reflectance properties of all surfaces in a real scene from a sparse set of photographs, taking into account both direct and indirect illumination. The result is a lighting-independent model of the scene’s geometry and reflectance properties, which can be rendered with arbitrary modifications to structure and lighting via traditional rendering methods. Our technique models reflectance with a low-parameter reflectance model, and allows diffuse albedo to vary arbitrarily over surfaces while assuming that non-diffuse characteristics remain constant across particular regions. The method’s input is a geometric model of the scene and a set of calibrated high dynamic range photographs taken with known direct illumination. The algorithm hierarchically partitions the scene into a polygonal mesh, and uses image-based rendering to construct estimates of both the radiance and irradiance of each patch from the photographic data. The algorithm computes the expected location of specular highlights, and then analyzes the highlight areas in the images by running a novel iterative optimization procedure to recover the diffuse and specular reflectance parameters for each region. Lastly, these parameters are used in constructing high-resolution diffuse albedo maps for each surface. The algorithm has been applied to both real and synthetic data, including a synthetic cubical room and a real meeting room. Re-renderings are produced using a global illumination system under both original and novel lighting, and with the addition of synthetic objects. Side-by-side comparisons show success at predicting the appearance of the scene under novel lighting conditions.


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