Abstract
We present a method to acquire the spatially varying reflectance properties of a human face and use these measurements to render the face under arbitrary changes in lighting and viewpoint. We first acquire a set of images of the face from two viewpoints under a dense sampling of incident illumination directions. We then construct a reflectance function image for each observed image pixel from its values over the space of illumination directions. From the reflectance functions, we can directly generate images of the face from the original viewpoints in any form of sampled or computed illumination. We then fit each pixel's reflectance function to a parameterized reflectance model adapted to experimental data so that the pixel's reflectance may be computed from novel viewpoints. We demonstrate our technique with synthetic renderings of a person's face under novel illumination and viewpoints.
Joint work with Tim Hawkins, Chris Tchou, H.P. Duiker, Westley Sarokin, and Mark Sagar