Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Vítor Sequeira"'
Publikováno v:
ICPR
In this paper we introduce a novel public dataset for developing and benchmarking indoor localization systems. We have selected and 3D mapped a set of representative indoor environments including a large office building, a conference room, a workshop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0ac53aee09eb82ae36b9f0898204589
https://doi.org/10.1109/icpr48806.2021.9413258
https://doi.org/10.1109/icpr48806.2021.9413258
Publikováno v:
ICRA
This paper presents a new technique to solve the Indoor Visual Place Recognition problem from the Deep Learning perspective. It consists on an image retrieval approach supported by a novel image similarity metric. Our work uses a 3D laser sensor moun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90b3755f40690802c46036f374d2328e
https://doi.org/10.1109/icra40945.2020.9196871
https://doi.org/10.1109/icra40945.2020.9196871
Publikováno v:
Computer Vision and Image Understanding. 149:197-208
We face the ego-motion estimation and localization in known large environments.A portable 3D sensor is used to solve the place recognition and tracking problems.An efficient search space reduction technique is proposed.Global localization is addresse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68fa8694333cc0aa4fde81035704789b
Publikováno v:
Intelligent Autonomous Systems 15 ISBN: 9783030013691
IAS
IAS
We present a robust Global Registration technique focused on environment survey applications using laser range-finders. Our approach works under the assumption that places can be recognized by analyzing the projection of the observed points along the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5060059b5a9f15f06868444ec3860387
https://doi.org/10.1007/978-3-030-01370-7_56
https://doi.org/10.1007/978-3-030-01370-7_56
Akademický článek
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Publikováno v:
Robotics and Autonomous Systems. 123:103324
We present a robust Global Matching technique focused on 3D mapping applications using laser range-finders. Our approach works under the assumption that places can be recognized by analyzing the projection of the observed points along the gravity dir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ac030427fde0cbe5d75b89d0805c678
https://doi.org/10.1016/j.robot.2019.103324
https://doi.org/10.1016/j.robot.2019.103324
Publikováno v:
Machine Vision and Applications. 24:305-318
We present a laser item identification system (L2IS), installed in a real facility on trial, that is capable of automatically monitoring all transfers of uranium hexafluoride (UF6) cylinders between different process areas. Each cylinder has a unique
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::895279bd61b5f0dd5ed84dd808f82fa7
https://doi.org/10.1007/s00138-011-0379-z
https://doi.org/10.1007/s00138-011-0379-z
Complex and photo-realistic scene representation based on range planar segmentation and model fusion
Publikováno v:
The International Journal of Robotics Research. 30:1263-1283
We present an efficient 3D scene representation method from a set of 3D range scans captured from a large-scale indoor or outdoor scene based on range planar segmentation and model fusion. In our method, range images are partitioned into planar patch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e29d66acdb338f92740c4e1147a63f7
https://doi.org/10.1177/0278364911410754
https://doi.org/10.1177/0278364911410754
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 63:55-67
This paper addresses the steps associated to reconstruct a model based on a number of scans acquired with different sensor techniques. It discusses the concept of managing and operating on scans with different origins, which may have different spatia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af6dc8429e07ce4efa42e67e7305dea6
https://doi.org/10.1016/j.isprsjprs.2007.07.011
https://doi.org/10.1016/j.isprsjprs.2007.07.011
Autor:
Vítor Sequeira, Antonio L. Rodriguez
Publikováno v:
ICCV
Ferns ensembles offer an accurate and efficient multiclass non-linear classification, commonly at the expense of consuming a large amount of memory. We introduce a two-fold contribution that produces large reductions in their memory consumption. Firs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a7e64a4d6dcd8709fe2a7c7ff97441d
https://doi.org/10.1109/iccv.2015.467
https://doi.org/10.1109/iccv.2015.467