Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Christoph Strecha"'
Publikováno v:
Remote Sensing of Environment. 229:60-68
A new physically based method to estimate hemispheric-directional reflectance factor (HDRF) from lightweight multispectral cameras that have a downwelling irradiance sensor is presented. It combines radiometry with photogrammetric computer vision to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::673ea1328fc23fbde218eb23812206bc
https://doi.org/10.1016/j.rse.2019.04.007
https://doi.org/10.1016/j.rse.2019.04.007
Autor:
Simon Rutishauser, Jonas Vautherin, Alexis Glass, Christoph Strecha, Hon Fai Choi, Klaus Schneider-Zapp, Venera Chovancova
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-3, Pp 139-146 (2016)
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences
Unmanned aerial vehicles (UAVs) are becoming increasingly popular in professional mapping for stockpile analysis, construction site monitoring, and many other applications. Due to their robustness and competitive pricing, consumer UAVs are used more
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31de88dc3fd25617b3ca9d1881a0b753
https://doi.org/10.5194/isprs-annals-iii-3-139-2016
https://doi.org/10.5194/isprs-annals-iii-3-139-2016
Publikováno v:
WHISPERS
To compute reflectance from images taken by multispectral sensors aboard UAVs, most users perform radiometric calibration using a target with known reflectance. This workflow is error-prone and not practical for large data acquisitions. With recent a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::942df7f89ae0f9b0dc2701bb5db01f8e
https://doi.org/10.1109/whispers.2018.8746910
https://doi.org/10.1109/whispers.2018.8746910
Autor:
François Gervaix, Jean-Christophe Zufferey, Antoine Beyeler, Dario Floreano, Christoph Strecha, Olivier Küng, Pascal Fua
Publikováno v:
Scopus-Elsevier
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXVIII-1/C22, Pp 125-130 (2012)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXVIII-1/C22, Pp 125-130 (2012)
This paper presents an affordable, fully automated and accurate mapping solutions based on ultra-light UAV imagery. Several datasets are analysed and their accuracy is estimated. We show that the accuracy highly depends on the ground resolution (flyi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7223be1aa27e6233b0ca3b79a56d95e
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-1-C22/125/2011/
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-1-C22/125/2011/
Autor:
V. Chovancova, L. Glassey, M. Krull, R. Zoller, B. Brot, Klaus Schneider-Zapp, Simon Rutishauser, Christoph Strecha
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol II-3/W4, Pp 215-222 (2015)
Recent mathematical advances, growing alongside the use of unmanned aerial vehicles, have not only overcome the restriction of roll and pitch angles during flight but also enabled us to apply non-metric cameras in photogrammetric method, providing mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0afae3e08ea59c2f2166e9030a7d90f0
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W4/215/2015/isprsannals-II-3-W4-215-2015.pdf
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W4/215/2015/isprsannals-II-3-W4-215-2015.pdf
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-1-W1, Pp 3-10 (2017)
We present a powerful method to extract per-point semantic class labels from aerialphotogrammetry data. Labeling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c171a28053e7e463fcc4218c58738714
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXVIII-1/C22, Pp 253-258 (2012)
Low cost mapping using UAV technology is becoming a trendy topic. Many systems exist where a simple camera can be deployed to take images, generally georeferenced with a GPS chip and MEMS attitude sensors. The step from using those images as informat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75dad74ee8d3ee7e80a72d801ee48d7c
https://doi.org/10.5194/isprsarchives-xxxviii-1-c22-253-2011
https://doi.org/10.5194/isprsarchives-xxxviii-1-c22-253-2011
Publikováno v:
Machine Vision and Applications. 23:903-920
We present a new approach for large-scale multi-view stereo matching, which is designed to operate on ultra high-resolution image sets and efficiently compute dense 3D point clouds. We show that, using a robust descriptor for matching purposes and hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5c5de6eee76607e5441d36354466f88
https://doi.org/10.1007/s00138-011-0346-8
https://doi.org/10.1007/s00138-011-0346-8
Autor:
Pascal Fua, Christoph Strecha, Mustafa Özuysal, Vincent Lepetit, Michael Calonder, Tomasz Trzcinski
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 34(7)
Binary descriptors are becoming increasingly popular as a means to compare feature points very fast while requiring comparatively small amounts of memory. The typical approach to creating them is to first compute floating-point ones, using an algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99dc9379f9d45d0f21948d5e6df94e8c
https://pubmed.ncbi.nlm.nih.gov/22084141
https://pubmed.ncbi.nlm.nih.gov/22084141
Publikováno v:
CVPR
Recent approaches to reconstructing city-sized areas from large image collections usually process them all at once and only produce disconnected descriptions of image subsets, which typically correspond to major landmarks. In contrast, we propose a f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edfbf5589cce96a7cc2bcac10ada3d5a
https://doi.org/10.1109/cvpr.2010.5540184
https://doi.org/10.1109/cvpr.2010.5540184