Sequentially-Defined Compressed Modes via ADMM

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dc.contributor.authorHouston, Kevinen_US
dc.contributor.editorJakob Andreas Bærentzen and Klaus Hildebrandten_US
dc.date.accessioned2017-07-02T17:44:34Z
dc.date.available2017-07-02T17:44:34Z
dc.date.issued2017
dc.description.abstractThe eigenfunctions of the discrete Laplace-Beltrami operator have played an important role in many aspects of geometry processing. Given the success of sparse representation methods in areas such as compressive sensing it is reasonable to find a sparse analogue of LBO eigenfunctions. This has been done by Ozolinš et al for Euclidean spaces and Neumann et al for surfaces where the resulting analogues are called compressed modes. In this short report we show that the method of Alternating Direction Method of Multipliers can be used to efficiently calculate compressed modes and that this compares well with a recent method to calculate them with an Iteratively Reweighted Least Squares method.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationSymposium on Geometry Processing 2017- Posters
dc.identifier.doi10.2312/sgp.20171201
dc.identifier.isbn978-3-03868-047-5
dc.identifier.issn1727-8384
dc.identifier.pages1-2
dc.identifier.urihttps://doi.org/10.2312/sgp.20171201
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/sgp20171201
dc.publisherThe Eurographics Associationen_US
dc.titleSequentially-Defined Compressed Modes via ADMMen_US
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