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Estimating Photometric Properties from Image Collections

Abstract : We address the problem of jointly estimating the scene illumination, the radiometric camera calibration and the reflectance properties of an object using a set of images from a community photo collection. The highly ill-posed nature of this problem is circumvented by using appropriate representations of illumination, an empirical model for the nonlinear function that relates image irradiance with intensity values and additional assumptions on the surface reflectance properties. Using a 3D model recovered from an unstructured set of images, we estimate the coefficients that represent the illumination for each image using a frequency framework. For each image, we also compute the corresponding camera response function. Additionally, we calculate a simple model for the reflectance properties of the 3D model. A robust non-linear optimization is proposed exploiting the high sparsity present in the problem.
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Contributor : Mauricio Díaz <>
Submitted on : Friday, May 24, 2013 - 10:08:47 AM
Last modification on : Thursday, November 19, 2020 - 1:00:34 PM

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Mauricio Díaz, Peter Sturm. Estimating Photometric Properties from Image Collections. Journal of Mathematical Imaging and Vision, Springer Verlag, 2013, 47 (1-2), pp.93-107. ⟨10.1007/s10851-013-0442-7⟩. ⟨hal-00825593⟩



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