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Perspective Shape from Shading : An Exposition on Recent Works with New Experiments

  • Shape from Shading (SFS) is a fundamental task in computer vision. By given information about the reflectance of an object’s surface and the position of the light source, the SFS problem is to reconstruct the 3D depth of the object from a single grayscale 2D input image. A modern class of SFS models relies on the property that the camera performs a perspective projection. The corresponding perspective SFS methods have been the subject of many investigations within the last years. The goal of this chapter is to give an overview of these developments. In our discussion, we focus on important model aspects, and we investigate some prominent algorithms appearing in the literature in more detail than it was done in previous works.

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Metadaten
Author: Michael BreußGND, Ashkan Mansouri Yarahmadi
DOI:https://doi.org/https://doi.org/10.1007/978-3-030-51866-0_2
ISBN:978-3-030-51865-3
ISBN:978-3-030-51866-0
ISSN:2191-6586
ISSN:2191-6594
Title of the source (English):Advances in Photometric 3D-Reconstruction
Publisher:Springer
Place of publication:Cham
Editor: Jean-Denis Durou, Maurizio Falcone, Yvain Quéau, Silvia Tozza
Document Type:Part of a book (chapter)
Language:English
Year of publication:2020
Tag:Shape from Shading Perspective projection Hamilton Jacobi equations Numerical methods Fast marching method
First Page:31
Last Page:72
Series ; volume number:Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)
Faculty/Chair:Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Angewandte Mathematik
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