RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES

We present a new relative pose estimation method for applications based on airborne image sequences. The performance of the method is tested using simulated test data, with correct and erroneous original conditions, as well as using real data. The calculated results obtained from real images are com...

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Main Authors: T. Reize, R. Müller, F. Kurz
Format: Article
Language:English
Published: Copernicus Publications 2012-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/57/2012/isprsannals-I-3-57-2012.pdf
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spelling doaj-7e60390b3f9d49a7b6c63df0dfd53c772020-11-24T21:17:50ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502012-07-01I-3576110.5194/isprsannals-I-3-57-2012RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCEST. Reize0R. Müller1F. Kurz2The Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, GermanyThe Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, GermanyThe Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, GermanyWe present a new relative pose estimation method for applications based on airborne image sequences. The performance of the method is tested using simulated test data, with correct and erroneous original conditions, as well as using real data. The calculated results obtained from real images are compared to the on-board measured angles. The results show that the proposed method is very precise and fast. Most matching algorithms are very computation time expensive mainly because they rely on RANSAC methods that need a lot of matching points. Due to the circumstance that only two corresponding points are necessary to solve the equation system, our technique doesn't need much computation time. Outliers are detected by a special back-matching technique. A method based on Polynomial Homotopy Continuation (PHC) is used to solve the complex polynomial equation system. The proposed pose solver method runs without SVD calculations, expensive minimisation or optimisation. Start parameters are not necessary. Furthermore, no a priori knowledge is required, besides focal length in pixel units and overlapping consecutive images. Outcomes are three relative orientation angles and a scaling parameter between two subsequent images, as well as displacement vectors in image pixel coordinate units. In addition, the PHC pose estimation method can balance small pixel errors. All these properties indicate the high applicability of the proposed method.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/57/2012/isprsannals-I-3-57-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author T. Reize
R. Müller
F. Kurz
spellingShingle T. Reize
R. Müller
F. Kurz
RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet T. Reize
R. Müller
F. Kurz
author_sort T. Reize
title RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
title_short RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
title_full RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
title_fullStr RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
title_full_unstemmed RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
title_sort relative pose estimation from airborne image sequences
publisher Copernicus Publications
series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 2194-9042
2194-9050
publishDate 2012-07-01
description We present a new relative pose estimation method for applications based on airborne image sequences. The performance of the method is tested using simulated test data, with correct and erroneous original conditions, as well as using real data. The calculated results obtained from real images are compared to the on-board measured angles. The results show that the proposed method is very precise and fast. Most matching algorithms are very computation time expensive mainly because they rely on RANSAC methods that need a lot of matching points. Due to the circumstance that only two corresponding points are necessary to solve the equation system, our technique doesn't need much computation time. Outliers are detected by a special back-matching technique. A method based on Polynomial Homotopy Continuation (PHC) is used to solve the complex polynomial equation system. The proposed pose solver method runs without SVD calculations, expensive minimisation or optimisation. Start parameters are not necessary. Furthermore, no a priori knowledge is required, besides focal length in pixel units and overlapping consecutive images. Outcomes are three relative orientation angles and a scaling parameter between two subsequent images, as well as displacement vectors in image pixel coordinate units. In addition, the PHC pose estimation method can balance small pixel errors. All these properties indicate the high applicability of the proposed method.
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/57/2012/isprsannals-I-3-57-2012.pdf
work_keys_str_mv AT treize relativeposeestimationfromairborneimagesequences
AT rmuller relativeposeestimationfromairborneimagesequences
AT fkurz relativeposeestimationfromairborneimagesequences
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