Partial Single- and Multishape Dense Correspondence Using Functional Maps

Or Litany, Emanuele Rodolà, Alex Bronstein, Michael Bronstein, Daniel Cremers

Publikation: Beitrag in Buch/Bericht/KonferenzbandKapitelBegutachtung

1 Zitat (Scopus)

Abstract

Shape correspondence is a fundamental problem in computer graphics and vision, with applications in various problems including animation, texture mapping, robotic vision, medical imaging, archaeology and many more. In settings where the shapes are allowed to undergo nonrigid deformations and only partial views are available, the problem becomes very challenging. In this chapter we describe recent techniques designed to tackle such problems. Specifically, we explain how the renown functional maps framework can be extended to tackle the partial setting. We then present a further extension to the multipart case in which one tries to establish correspondence between a collection of shapes. Finally, we focus on improving the technique efficiency, by disposing of its spatial ingredient and thus keeping the computation in the spectral domain. Extensive experimental results are provided along with the theoretical explanations, to demonstrate the effectiveness of the described methods in these challenging scenarios.

OriginalspracheEnglisch
TitelProcessing, Analyzing and Learning of Images, Shapes, and Forms
UntertitelPart 1
Redakteure/-innenRon Kimmel, Xue-Cheng Tai
Herausgeber (Verlag)Elsevier B.V.
Seiten55-90
Seitenumfang36
ISBN (Print)9780444642059
DOIs
PublikationsstatusVeröffentlicht - 2018

Publikationsreihe

NameHandbook of Numerical Analysis
Band19
ISSN (Print)1570-8659

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