Beyond Lambert: reconstructing surfaces with arbitrary BRDFs

Abstract

We address an open and hitherto neglected problem in computer vision, how to reconstruct the geometry of objects with arbitrary and possibly anisotropic bidi- rectional reflectance distribution functions (BRDFs). Present reconstruction techniques, whether stereo vi- sion, structure from motion, laser range finding, etc. make explicit or implicit assumptions about the BRDF. Here, we introduce two methods that were developed by re-examining the underlying image formation pro- cess; the methods make no assumptions about the ob- ject's shape, the presence or absence of shadowing, or. the nature of the BRDF which may vary over the sur- face. The first method takes advantage of Helmholtz reciprocity, while the second method exploits the fact that the, radiance along a ray of light is constant. In particular, the first method uses stereo pairs of images in which point light sources are co-located at the cen- ters of projection of the stereo cameras. The second method is based on double covering a scene's incident light field; the depths of surface points are estimated using a large collection of images in which the view- point remains fixed and a point light source illuminates the object. Results from our implementations lend em- pirical support to both techniques.