A Multiple-View Geometric Model of Specularities on Non-Planar Shapes with Application to Dynamic Retexturing

Predicting specularities in images, given the camera pose and scene geometry from SLAM, forms a challenging and open problem. It is nonetheless essential in several applications such as retexturing. A recent geometric model called JOLIMAS partially answers this problem, under the assumptions that th...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 23(2017), 11 vom: 28. Nov., Seite 2485-2493
1. Verfasser: Morgand, Alexandre (VerfasserIn)
Weitere Verfasser: Tamaazousti, Mohamed, Bartoli, Adrien
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2017
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:Predicting specularities in images, given the camera pose and scene geometry from SLAM, forms a challenging and open problem. It is nonetheless essential in several applications such as retexturing. A recent geometric model called JOLIMAS partially answers this problem, under the assumptions that the specularities are elliptical and the scene is planar. JOLIMAS models a moving specularity as the image of a fixed 3D quadric. We propose dual JOLIMAS, a new model which raises the planarity assumption. It uses the fact that specularities remain elliptical on convex surfaces and that every surface can be divided in convex parts. The geometry of dual JOLIMAS then uses a 3D quadric per convex surface part and light source, and predicts the specularities by a means of virtual cameras, allowing it to cope with surface's unflatness. We assessed the efficiency and precision of dual JOLIMAS on multiple synthetic and real videos with various objects and lighting conditions. We give results of a retexturing application. Further results are presented as supplementary video material
Beschreibung:Date Completed 11.12.2018
Date Revised 11.12.2018
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2017.2734538