Imperial College London

ProfessorMichaelBronstein

Faculty of EngineeringDepartment of Computing

Chair in Machine Learning and Pattern Recognition
 
 
 
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Contact

 

m.bronstein Website

 
 
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Location

 

569Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Litany:2018:10.1016/bs.hna.2018.09.002,
author = {Litany, O and RodolĂ , E and Bronstein, A and Bronstein, M and Cremers, D},
doi = {10.1016/bs.hna.2018.09.002},
journal = {Handbook of Numerical Analysis},
pages = {55--90},
title = {Partial Single- and Multishape Dense Correspondence Using Functional Maps},
url = {http://dx.doi.org/10.1016/bs.hna.2018.09.002},
volume = {19},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - © 2018 Elsevier B.V. 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.
AU - Litany,O
AU - RodolĂ ,E
AU - Bronstein,A
AU - Bronstein,M
AU - Cremers,D
DO - 10.1016/bs.hna.2018.09.002
EP - 90
PY - 2018///
SN - 1570-8659
SP - 55
TI - Partial Single- and Multishape Dense Correspondence Using Functional Maps
T2 - Handbook of Numerical Analysis
UR - http://dx.doi.org/10.1016/bs.hna.2018.09.002
VL - 19
ER -