Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Nadisson Luis Pavan"'
Autor:
Rubens Antônio Leite Benevides, Daniel Rodrigues dos Santos, Nadisson Luis Pavan, Luis Augusto Koenig Veiga
Publikováno v:
Sensors, Vol 24, Iss 16, p 5112 (2024)
Global pose refinement is a significant challenge within Simultaneous Localization and Mapping (SLAM) frameworks. For LIDAR-based SLAM systems, pose refinement is integral to correcting drift caused by the successive registration of 3D point clouds c
Externí odkaz:
https://doaj.org/article/e9a4627199b543efa03b21d7cdaca55d
Publikováno v:
Revista Brasileira de Cartografia, Vol 76, Iss 0a (2024)
O registro de nuvens de pontos 3D e o refinamento global de poses são dois problemas fundamentais ao realizar o Mapeamento e Localização Simultâneos (Simultaneous Localization and Mapping - SLAM) com sensores LIDAR. O registro de nuvens consiste
Externí odkaz:
https://doaj.org/article/1ea393e63b9440d3ad8c006327a2de3b
Publikováno v:
Remote Sensing, Vol 12, Iss 7, p 1127 (2020)
Registration of point clouds is a central problem in many mapping and monitoring applications, such as outdoor and indoor mapping, high-speed railway track inspection, heritage documentation, building information modeling, and others. However, ensuri
Externí odkaz:
https://doaj.org/article/a82e5eedeea34a5690cbb86f45e11a34
Publikováno v:
Revista Brasileira de Cartografia, Vol 70, Iss 1 (2018)
Neste trabalho é apresentado um método para registro de pares de nuvens de pontos 3D derivados do sistema LASER scanner terrestre usando linhas retas e planos. A principal contribuição deste trabalho é o modelo linear proposto para estimativa do
Externí odkaz:
https://doaj.org/article/363362b58b7543238d06603a72961dc6
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-1, Pp 121-125 (2018)
Terrestrial laser scanner (TLS) sensor captures highly dense and accurate point clouds quite useful for indoor and outdoor mapping, navigation, 3D reconstruction, surveillance, industrial projects, infrastructure management, and others. In this paper
Autor:
Daniel Santos, Nadisson Luis Pavan
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 14:1131-1135
Existing global registration methods are prominently iterative. They require iterations and can be sensitive to point densities and noise. In contrast, closed-form solutions provide a more robust estimation model and do not involve iterations. In thi
Autor:
Kourosh Khoshelham, Nadisson Luis Pavan, Marcos Aurélio Basso, George Vosselman, Elizeu Martins de Oliveira, Daniel Santos
Publikováno v:
IEEE geoscience and remote sensing letters, 13(2), 262-266. IEEE
In this letter, we present an adaptive coarse-to-fine registration method for 3-D indoor mapping using RGB-D data. We weight the 3-D points based on the theoretical random error of depth measurements and introduce a novel disparity-based model for an
Publikováno v:
Remote Sensing; Volume 12; Issue 7; Pages: 1127
Remote Sensing, Vol 12, Iss 1127, p 1127 (2020)
Remote Sensing, Vol 12, Iss 1127, p 1127 (2020)
Registration of point clouds is a central problem in many mapping and monitoring applications, such as outdoor and indoor mapping, high-speed railway track inspection, heritage documentation, building information modeling, and others. However, ensuri
Publikováno v:
Revista Brasileira de Cartografia, Vol 70, Iss 1 (2018)
Neste trabalho é apresentado um método para registro de pares de nuvens de pontos 3D derivados do sistema LASER scanner terrestre usando linhas retas e planos. A principal contribuição deste trabalho é o modelo linear proposto para estimativa do
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B3, Pp 403-409 (2016)
Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b6fdc6b7908d8e499711108a4d8f5d8
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/403/2016/
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/403/2016/