Photometric reconstruction is the process of estimating the illumination and surface reflectance properties of an environment, given a geometric model of the scene and a set of photographs of its surfaces. For mixed-reality applications, such data is required if synthetic objects are to be correctly illuminated or if synthetic light sources are to be used to re-light the scene. Current methods of estimating such data are limited in the practical situations in which they can be applied, due to the fact that the geometric and radiometric models of the scene which are provided by the user must be complete, and that the position (and in some cases, intensity) of the light sources must also be specified a-priori. In this paper, a novel algorithm is presented which overcomes these constraints, and allows photometric data to be reconstructed in less restricted situations. This is achieved through the use of virtual light sources which mimic the effect of direct illumination from unknown luminaires, and indirect illumination reflected off unknown geometry. The intensity of these virtual light sources and the surface material properties are estimated using an iterative algorithm which attempts to match calculated radiance values to those observed in photographs. Results are presented for both synthetic and real scenes that show the quality of the reconstructed data and its use in off-line mixed-reality applications.
['Simon Gibson', 'Toby Howard', 'Roger J. Hubbold']
Flexible Image-Based Photometric Reconstruction using Virtual Light Sources