Recovering 3-D Shape and Reflectance from a Small Number of Photographs



Abstract  There are computer graphics applications for which the shape and reflectance of complex objects, such as faces, cannot be obtained using specialized equipment due to cost and practical considerations. We present an imagebased technique that uses only a small number of example images, and assumes a parametric model of reflectance, to simultaneously and reliably recover the Bidirectional Reflectance Distribution Function (BRDF) and the 3-D shape of non-Lambertian objects. No information about the position and intensity of the light-sources or the position of the camera is required. We successfully apply this approach to human faces, accurately recovering their 3-D shape and BRDF. We use the recovered information to efficiently and accurately render photorealistic images of the faces under novel illumination conditions in which the rendered image intensity closely matches the intensity in real images. The accuracy of our technique is further demonstrated by the close resemblance of the skin BRDF recovered using our method, to the one measured with a method presented in the literature and in which a 3-D scanner was used.