Autor segons l'article: Sanroma, Gerard; Penate-Sanchez, Adrian; Alquezar, Rene; Serratosa, Francesc; Moreno-Noguer, Francesc; Andrade-Cetto, Juan; Gonzalez Ballester, Miguel Angel
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Serratosa Casanelles, Francesc d'Assís
Paraules clau: Writing Vision Theoretical model Priors Models, theoretical Graph Extract Distance Algorithms Algorithm
Resum: We present a novel approach for feature correspondence and multiple structure discovery in computer vision. In contrast to existing methods, we exploit the fact that point-sets on the same structure usually lie close to each other, thus forming clusters in the image. Given a pair of input images, we initially extract points of interest and extract hierarchical representations by agglomerative clustering. We use the maximum weighted clique problem to find the set of corresponding clusters with maximum number of inliers representing the multiple structures at the correct scales. Our method is parameter-free and only needs two sets of points along with their tentative correspondences, thus being extremely easy to use. We demonstrate the effectiveness of our method in multiple-structure fitting experiments in both publicly available and in-house datasets. As shown in the experiments, our approach finds a higher number of structures containing fewer outliers compared to state-of-the-art methods. © 2016 Sanroma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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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: 2024-10-12
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0145846
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Plos One. 11 (1): e0145846-
Referència de l'ítem segons les normes APA: Sanroma, Gerard; Penate-Sanchez, Adrian; Alquezar, Rene; Serratosa, Francesc; Moreno-Noguer, Francesc; Andrade-Cetto, Juan; Gonzalez Ballester, Miguel (2016). MSClique: Multiple structure discovery through the maximum weighted clique problem. Plos One, 11(1), e0145846-. DOI: 10.1371/journal.pone.0145846
DOI de l'article: 10.1371/journal.pone.0145846
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2016
Tipus de publicació: Journal Publications
Repositori URV