Title: Original strategy for avoiding over-smoothing in SFS problem resolution

Authors: Rocco Furferi; Lapo Governi; Yary Volpe; Luca Puggelli; Monica Carfagni

Addresses: Department of Industrial Engineering, University of Florence, Via di Santa Marta, 3 50134 Firenze, Italy ' Department of Industrial Engineering, University of Florence, Via di Santa Marta, 3 50134 Firenze, Italy ' Department of Industrial Engineering, University of Florence, Via di Santa Marta, 3 50134 Firenze, Italy ' Department of Industrial Engineering, University of Florence, Via di Santa Marta, 3 50134 Firenze, Italy ' Department of Industrial Engineering, University of Florence, Via di Santa Marta, 3 50134 Firenze, Italy

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.

Keywords: shape from shading; SFS; variational approach; 3D model; smoothing; minimisation; smoothness constraint.

DOI: 10.1504/IJCVR.2018.090016

International Journal of Computational Vision and Robotics, 2018 Vol.8 No.1, pp.58 - 73

Received: 22 Apr 2016
Accepted: 27 Apr 2016

Published online: 04 Oct 2017 *

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