Autor segons l'article: Moreno-García C; Serratosa F
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: MORENO GARCIA, CARLOS FRANCISCO / Serratosa Casanelles, Francesc d'Assís
Paraules clau: Munkres algorithm Graph edit distance Bipartite graph matching
Resum: 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: francesc.serratosa@urv.cat
Identificador de l'autor: 0000-0001-6112-5913
Data d'alta del registre: 2024-09-07
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Pattern Analysis And Applications. 20 (1): 201-213
Referència de l'ítem segons les normes 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
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2017
Tipus de publicació: Journal Publications