Author, as appears in the article.: Moreno-García C; Serratosa F
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: MORENO GARCIA, CARLOS FRANCISCO / Serratosa Casanelles, Francesc d'Assís
Keywords: Munkres algorithm Graph edit distance Bipartite graph matching
Abstract: We present a consensus method which, given the two correspondences between sets of elements generated by separate entities, enounces a final correspondence consensus considering the existence of outliers. Our method is based on an optimisation technique that minimises the cost of the correspondence while forcing (to the most) to be the mean correspondence of the two original correspondences. The method decides the mapping of the elements that the original correspondences disagree and returns the same element mapping when both correspondences agree. We first show the validity of the method through an experiment in ideal conditions based on palmprint identification, and subsequently present two practical experiments based on image retrieval.
Thematic Areas: Medicina i Matemática / probabilidade e estatística Interdisciplinar Engenharias iv Computer vision and pattern recognition Computer science, artificial intelligence Ciências biológicas i Ciência da computação Artificial intelligence Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: francesc.serratosa@urv.cat
Author identifier: 0000-0001-6112-5913
Record's date: 2024-09-07
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://link.springer.com/article/10.1007/s10044-015-0486-y
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Pattern Analysis And Applications. 20 (1): 201-213
APA: Moreno-García C; Serratosa F (2017). Correspondence consensus of two sets of correspondences through optimisation functions. Pattern Analysis And Applications, 20(1), 201-213. DOI: 10.1007/s10044-015-0486-y
Article's DOI: 10.1007/s10044-015-0486-y
Entity: Universitat Rovira i Virgili
Journal publication year: 2017
Publication Type: Journal Publications