Shape and View Independent Reflectance mAP from Multiple Views

Abstract

We consider the problem of estimating the 3D shape and reflectance properties of an object made of a single material from a calibrated set of multiple views. To model reflectance, we propose a View Independent Reflectance Map (VIRM) and derive it from Torrance-Sparrow BRDF model. Reflectance estimation then amounts to estimating VIRM parameters. We represent object shape using surface triangulation. We pose the estimation problem as one of minimizing cost of matching input images, and the images synthesized using shape and reflectance estimates. We show that by enforcing a constant value of VIRM as a global constraint, we can minimize the matching cost function by iterating between VIRM and shape estimation. Experiment results on both synthetic and real objects show that our algorithm is effective in recovering the 3D shape as well as non-lambertian reflectance information. Our algorithm does not require that light sources be known or calibrated using special objects, thus making it more flexible than other photometric stereo or shape from shading methods. The estimated VIRM can be used to synthesize views of other objects.