Evaluation of feature-based methods for automated network orientation
Every day new tools and algorithms for automated image processing and 3D reconstruction purposes become available, giving the possibility to process large networks of unoriented and markerless images, delivering sparse 3D point clouds at reasonable processing time. In this paper we evaluate some f...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-5/47/2014/isprsarchives-XL-5-47-2014.pdf |
| Summary: | Every day new tools and algorithms for automated image processing and 3D reconstruction purposes become available, giving the
possibility to process large networks of unoriented and markerless images, delivering sparse 3D point clouds at reasonable
processing time. In this paper we evaluate some feature-based methods used to automatically extract the tie points necessary for
calibration and orientation procedures, in order to better understand their performances for 3D reconstruction purposes. The
performed tests – based on the analysis of the SIFT algorithm and its most used variants – processed some datasets and analysed
various interesting parameters and outcomes (e.g. number of oriented cameras, average rays per 3D points, average intersection
angles per 3D points, theoretical precision of the computed 3D object coordinates, etc.). |
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| ISSN: | 1682-1750 2194-9034 |