Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Adrian Penate-Sanchez"'
Autor:
Adrian Penate-Sanchez, Lourdes Agapito
Publikováno v:
IEEE Access, Vol 8, Pp 35696-35711 (2020)
We propose a new approach to perform object shape retrieval from images, it can handle the shape of the part of the object and combine parts from different sources to find a different 3D shape. Our method creates a common representation for images an
Externí odkaz:
https://doaj.org/article/5e5fe1252f8e434196b0aeec37ea516a
Autor:
Gerard Sanroma, Adrian Penate-Sanchez, René Alquézar, Francesc Serratosa, Francesc Moreno-Noguer, Juan Andrade-Cetto, Miguel Ángel González Ballester
Publikováno v:
PLoS ONE, Vol 11, Iss 1, p e0145846 (2016)
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 clust
Externí odkaz:
https://doaj.org/article/b07113ceeee149f199306a08825e420d
Autor:
Modesto Castrillón-Santana, Pedro A. Marín-Reyes, Adrian Penate-Sanchez, Kevin Rosales-Santana, David Freire-Obregón, Javier Lorenzo-Navarro
Publikováno v:
Pattern Recognition Letters. 149:179-184
In this paper, we tackle the task of improving biometric verification in the context of Human-Robot Interaction (HRI). A robot that wants to identify a specific person to provide a service can do so by either image verification or, if light condition
Autor:
Adrian Penate-Sanchez, David Freire-Obregón, Modesto Castrillón-Santana, Adrián Lorenzo-Melián, Javier Lorenzo-Navarro
Publikováno v:
Pattern Recognition Letters. 138:355-361
Person re-identification (Re-ID) is the task of retrieving a person of interest taken from different cameras or from the same camera in different occasions. To address this challenging task, a large amount of labelled data is required both for testin
Autor:
Javier Lorenzo-Navarro, Modesto Castrillón-Santana, David Freire-Obregón, Adrian Penate-Sanchez, Pablo Hernandez-Carrascosa
Publikováno v:
ICPR
Racing bib number (RBN) detection and recognition is a specific problem related to text recognition in natural scenes. In this paper, we present a novel dataset created after registering participants in a real ultrarunning competition which comprises
Autor:
Adrian Penate-Sanchez
In this article, we reflect on the variables to be considered when teaching in English a subject of the bachelor’s degree of Computer Engineering: “Learning Professional Skills for Engineers”. In order to make this study, we start from an analy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0d57bb0c429ff5b69b9e715f9150f7c
Localization in challenging, natural environments such as forests or woodlands is an important capability for many applications from guiding a robot navigating along a forest trail to monitoring vegetation growth with handheld sensors. In this work w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37a77408597776a2ac30a595e05d3780
https://ora.ox.ac.uk/objects/uuid:e181235e-f4e4-408d-8235-6899d922bf59
https://ora.ox.ac.uk/objects/uuid:e181235e-f4e4-408d-8235-6899d922bf59
Autor:
Lourdes Agapito, Adrian Penate-Sanchez
Publikováno v:
IEEE Access
IEEE Access, Vol 8, Pp 35696-35711 (2020)
IEEE Access, Vol 8, Pp 35696-35711 (2020)
We propose a new approach to perform object shape retrieval from images, it can handle the shape of the part of the object and combine parts from different sources to find a different 3D shape. Our method creates a common representation for images an
Autor:
Adrian Penate-Sanchez, Lourdes Agapito
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208868
ACCV (1)
ACCV (1)
We present 3D Pick & Mix, a new 3D shape retrieval system that provides users with a new level of freedom to explore 3D shape and Internet image collections by introducing the ability to reason about objects at the level of their constituent parts. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0292c56c17b276aac7be5d9a61093b0
https://doi.org/10.1007/978-3-030-20887-5_10
https://doi.org/10.1007/978-3-030-20887-5_10