We present a technique for recovering spatially varying reflectance parameters of real environments from photographs taking into account mutual illumination. The techniques fits to a low-parameter reflectance model, allowing diffuse albedo to vary over a surface while constraining specular parameters to be constant over individual surfaces. The method's input is a geometric model of the scene and a set of calibrated high dynamic range photographs taken with known light source positions. The algorithm begins by hierarchically partitioning the scene into a polygon mesh. From the photographic data, the algorithm uses image-based rendering to construct estimates of both the radiance and directional irradiance of each patch. The algorithm computes the expected location of specular highlights, and then analyzes the the highlight areas in the images to determine specular color and roughness parameters for each region. The specular reflectance estimates are then used to iteratively re-estimate the patch radiances and irradiances. With these final estimates of irradiance, the image data is used to construct high-resolution diffuse albedo maps for each surface. The result is a lighting-independent model of the scene's geometry and material properties, which can be rendered using traditional graphics methods. We apply the algorithm to both real and synthetic data, including a model of a real room exhibiting significant mutual illumination. Reflectance models including spatially varying diffuse properties for the entire scene are recovered. The algorithm is shown to successfully account for the effects of both specular and diffuse interreflection. Realistic re-renderings are produced using a global illumination algorithm 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. 1
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