Model Evaluation and Measurement Optimization for the Reproduction of Artist Paint Surfaces through Computer Graphics Renderings

Light reflection models for computer graphics have been developed over the past several decades. For real paint surfaces, it is possible to model their bidirectional reflectance distribution function with simple models. A framework was established to evaluate two simple reflection models, Phong and Torrance-Sparrow, which were used to render artist paint surfaces under different illumination angles. An image acquisition system was devised to capture the images under selected illuminated angles. The parameters of the specular and the diffuse components were estimated with these image sequences. At the evaluation stage, both physicallybased metrics and psychophysical techniques were used to evaluate the estimation accuracy of each model. For both methods, the comparison of the estimations of the two models showed that better estimations were obtained from the Torrance-Sparrow model for glossy samples. The estimation accuracies of the two models were almost the same for matte samples. In addition, based on the analyses of the specular peak width and the histogram of the peak values, the optimized location and minimal number ofmeasurements were determinedfor four kinds ofpaint samples