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PiMPeR: Piecewise Dense 3D Reconstruction from Multi-View and Multi-Illumination Images by Sabzevari, Reza; Murino, Vittori; Del Bue, Alessio is a scholarly article available to read on EtoBox.

What is PiMPeR: Piecewise Dense 3D Reconstruction from Multi-View and Multi-Illumination Images about?

In this paper, we address the problem of dense 3D reconstruction from multiple view images subject to strong lighting variations. In this regard, a new piecewise framework is proposed to explicitly take into account the change of illumination across several wide-baseline images. Unlike multi-view stereo and multi-view photometric stereo methods, this pipeline deals with wide-baseline images that are uncalibrated, in terms of both camera parameters and lighting conditions. Such a scenario is meant to avoid use of any specific imaging setup and provide a tool for normal users without any expertise. To the best of our knowledge, this paper presents the first work that deals with such unconstrained setting. We propose a coarse-to-fine approach, in which a coarse mesh is first created using a set of geometric constraints and, then, fine details are recovered by exploiting photometric properties of the scene. Augmenting the fine details on the coarse mesh is done via a final optimization step. Note that the method does not provide a generic solution for multi-view photometric stereo problem but it relaxes several common assumptions of this problem. The approach scales very well in size g

Author

Sabzevari, Reza; Murino, Vittori; Del Bue, Alessio

Published

2015

Language

EN