English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/96685
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Title

Smooth point-set registration using neighboring constraints

AuthorsSanroma, Gerard; Alquézar Mancho, Renato ; Serratosa, Francesc; Herrera, Blas
KeywordsSoftassing
Point-set registration
Correspondence problem
Graph matching
Issue Date2012
PublisherElsevier
CitationPattern Recognition Letters 33(15): 2029-2037 (2012)
AbstractWe present an approach for Maximum Likelihood estimation of correspondence and alignment parameters that benefits from the representational skills of graphs. We pose the problem as one of mixture modeling within the framework of the Expectation-Maximization algorithm. Our mixture model encompasses a Gaussian density to model the point-position errors and a Bernoulli density to model the structural errors. The Gaussian density components are parameterized by the alignment parameters which constrain their means to move according to a similarity transformation model. The Bernoulli density components are parameterized by the continuous correspondence indicators which are updated within an annealing procedure using Softassign. Outlier rejection is modeled as a gradual assignment to the null node. We highlight the analogies of our method to some existing methods. We investigate the benefits of using structural and geometrical information by presenting results of the full rigid version of our method together with its pure geometrical and its pure structural versions. We compare our method to other point-set registration methods as well as to other graph matching methods which incorporate geometric information. We also present a non-rigid version of our method and compare to state-of-the-art non-rigid registration methods. Results show that our method gets either the best performance or similar performance than state-of-the-art methods. © 2012 Elsevier B.V. All rights reserved.
Publisher version (URL)http://dx.doi.org/10.1016/j.patrec.2012.04.008
URIhttp://hdl.handle.net/10261/96685
DOI10.1016/j.patrec.2012.04.008
Identifiersdoi: 10.1016/j.patrec.2012.04.008
issn: 0167-8655
Appears in Collections:(IRII) Artículos
Files in This Item:
File Description SizeFormat 
Smooth point-set.pdf555,1 kBUnknownView/Open
Show full item record
Review this work
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.