Title: Improving surface reconstruction in shape from shading using easy-to-set boundary conditions

Authors: L. Governi; R. Furferi; L. Puggelli; Y. Volpe

Addresses: Department of Industrial Engineering, University of Florence, via S. Marta, 50139 Firenze, Italy ' Department of Industrial Engineering, University of Florence, via S. Marta, 50139 Firenze, Italy ' Department of Industrial Engineering, University of Florence, via S. Marta, 50139 Firenze, Italy ' Department of Industrial Engineering, University of Florence, via S. Marta, 50139 Firenze, Italy

Abstract: Minimisation techniques are commonly adopted methodologies for retrieving a 3D surface starting from its shaded representation (image), i.e., for solving the widely known shape from shading (SFS) problem. Unfortunately, depending on the imaged object to be reconstructed, retrieved surfaces often results to be completely different from the expected ones. In recent years, a number of interactive methods have been explored with the aim of improving surface reconstruction; however, since most of these methods require user interaction performed on a tentative reconstructed surface which often is significantly different from the desired one, it is advisable to increase the quality of the surface, to be further processed, as much as possible. Inspired by such techniques, the present work describes a new method for interactive retrieving of shaded object surface. The proposed approach is meant to recover the expected surface by using easy-to-set boundary conditions, so that the human-computer interaction primarily takes place prior to the surface retrieval. The method, tested on a set of case studies, proves to be effective in achieving sufficiently accurate reconstruction of scenes with both front and side illumination.

Keywords: shape from shading; SFS; minimisation techniques; computational vision; boundary conditions; human-computer interaction; HCI; surface reconstruction; 3D surfaces; shaded objects; object surfaces; surface retrieval.

DOI: 10.1504/IJCVR.2013.056041

International Journal of Computational Vision and Robotics, 2013 Vol.3 No.3, pp.225 - 247

Received: 11 Mar 2013
Accepted: 24 May 2013

Published online: 24 Aug 2013 *

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