Original strategy for avoiding over-smoothing in SFS problem resolution. (2018)

• Record Type: Journal Article
• Authors: Furferi, Rocco; Governi, Lapo; Volpe, Yary; Puggelli, Luca; Carfagni, Monica
• Is Part Of: International journal of computational vision and robotics. Volume 8:Number 1(2018)
• Page Start: 58
• Page End: 73
• Publication Date: 2018
• Subjects: shape from shading -- SFS -- variational approach -- 3D model -- smoothing -- minimisation -- smoothness constraint; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

With the aim of retrieving 3D surfaces starting from single shaded images, i.e. for solving the widely known shape from shading problem, an important class of methods is based on minimisation techniques where the expected surface to be retrieved is supposed to be coincident with the one that minimise a properly developed functional, consisting of several contributions. Despite several different contributes that can be explored to define a functional, the so called 'smoothness constraint' is a cornerstone since it is the most relevant contribute to guide the convergence of the minimisation process towards a more accurate solution. Unfortunately, in case input shaded image is characterised by areas where actual brightness changes rapidly, such a constraint introduces an undesired over-smoothing effect for the retrieved surface. The present work proposes an original strategy for avoiding such a typical over-smoothing effect, with regard to the image regions in which this is particularly undesired such as, for instance, zones where surface details are to be preserved in the reconstruction. The proposed strategy is tested against a set of case studies and compared with other traditional SFS based methods to prove its effectiveness.