Shape from shading by model inclusive learning with simultaneously estimating reflection parameters

Abstract

Recovering shape from shading is an important problem in computer vision and robotics and many studies have been done. We have already proposed a versatile method of solving the problem by model inclusive learning of neural networks. The method is versatile in the sense that it can solve the problem in various circumstances. Almost all of the methods of recovering shape from shading proposed so far assume that surface reflection properties of a target object are known a priori. It is, however, very difficult to obtain those properties exactly. In this paper we propose a method to resolve this problem by extending our previous method. The proposed method makes it possible to recover shape with simultaneously estimating reflection parameters of an object. © 2014 Springer International Publishing Switzerland.