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K. Vanhoey, B. Sauvage, O. Génevaux, F. Larue and J.-M. Dischler Robust Fitting on Poorly Sampled Data for Surface Light Field Rendering and Image Relighting Computer Graphics Forum 32

Version of Record online: 1 APR 2013 | DOI: 10.1111/cgf.12073

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Generating surface light fields from real acquisition campaigns' data often leads to robustness issues that are due to irregular distribution and sparsity of the photographic sampling. Within this context, we present a robust least-squares-based method for fitting 2D parametric colour functions on sparse and scattered data. Moreover, we provide a statistical analysis to measure the robustness of such fitting approaches. The proposed method allows, on one hand, for high-quality reconstructions in good sampling conditions and, on the other hand, for robust and predictable reconstructions in poor sampling conditions.

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