EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES

For autonomous navigation of micro aerial vehicles (MAVs), a robust detection of obstacles with onboard sensors is necessary in order to avoid collisions. Cameras have the potential to perceive the surroundings of MAVs for the reconstruction of their 3D structure. We equipped our MAV with two fishey...

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Main Authors: N. Krombach, D. Droeschel, S. Behnke
Format: Article
Language:English
Published: Copernicus Publications 2015-08-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-1-W1/33/2015/isprsannals-II-1-W1-33-2015.pdf
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spelling doaj-dfb6285632dc43ffbfeb6f2674580d8b2020-11-25T01:06:23ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502015-08-01II-1/W1334010.5194/isprsannals-II-1-W1-33-2015EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSESN. Krombach0D. Droeschel1S. Behnke2Autonomous Intelligent Systems Group, Institute for Computer Science VI, University of Bonn, Bonn, GermanyAutonomous Intelligent Systems Group, Institute for Computer Science VI, University of Bonn, Bonn, GermanyAutonomous Intelligent Systems Group, Institute for Computer Science VI, University of Bonn, Bonn, GermanyFor autonomous navigation of micro aerial vehicles (MAVs), a robust detection of obstacles with onboard sensors is necessary in order to avoid collisions. Cameras have the potential to perceive the surroundings of MAVs for the reconstruction of their 3D structure. We equipped our MAV with two fisheye stereo camera pairs to achieve an omnidirectional field-of-view. Most stereo algorithms are designed for the standard pinhole camera model, though. Hence, the distortion effects of the fisheye lenses must be properly modeled and model parameters must be identified by suitable calibration procedures. In this work, we evaluate the use of real-time stereo algorithms for depth reconstruction from fisheye cameras together with different methods for calibration. In our experiments, we focus on obstacles occurring in urban environments that are hard to detect due to their low diameter or homogeneous texture.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-1-W1/33/2015/isprsannals-II-1-W1-33-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author N. Krombach
D. Droeschel
S. Behnke
spellingShingle N. Krombach
D. Droeschel
S. Behnke
EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet N. Krombach
D. Droeschel
S. Behnke
author_sort N. Krombach
title EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
title_short EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
title_full EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
title_fullStr EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
title_full_unstemmed EVALUATION OF STEREO ALGORITHMS FOR OBSTACLE DETECTION WITH FISHEYE LENSES
title_sort evaluation of stereo algorithms for obstacle detection with fisheye lenses
publisher Copernicus Publications
series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 2194-9042
2194-9050
publishDate 2015-08-01
description For autonomous navigation of micro aerial vehicles (MAVs), a robust detection of obstacles with onboard sensors is necessary in order to avoid collisions. Cameras have the potential to perceive the surroundings of MAVs for the reconstruction of their 3D structure. We equipped our MAV with two fisheye stereo camera pairs to achieve an omnidirectional field-of-view. Most stereo algorithms are designed for the standard pinhole camera model, though. Hence, the distortion effects of the fisheye lenses must be properly modeled and model parameters must be identified by suitable calibration procedures. In this work, we evaluate the use of real-time stereo algorithms for depth reconstruction from fisheye cameras together with different methods for calibration. In our experiments, we focus on obstacles occurring in urban environments that are hard to detect due to their low diameter or homogeneous texture.
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-1-W1/33/2015/isprsannals-II-1-W1-33-2015.pdf
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