Evaluations on multi-scale camera networks for precise and geo-accurate reconstructions from aerial and terrestrial images with user guidance
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In: Computer Vision and Image Understanding, 2016.
Research output: Contribution to journal › Article › Research › peer-review
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TY - JOUR
T1 - Evaluations on multi-scale camera networks for precise and geo-accurate reconstructions from aerial and terrestrial images with user guidance
AU - Rumpler, Markus
AU - Tscharf, Alexander
AU - Mostegel, Christian
AU - Daftry, Shreyansh
AU - Hoppe, Christof
AU - Prettenthaler, Rudolf
AU - Fraundorfer, Friedrich
AU - Mayer, Gerhard
AU - Bischof, Horst
PY - 2016
Y1 - 2016
N2 - Abstract During the last decades photogrammetric computer vision systems have been well established in scientific and commercial applications. Recent developments in image-based 3D reconstruction systems have resulted in an easy way of creating realistic, visually appealing and accurate 3D models. We present a fully automated processing pipeline for metric and geo-accurate 3D reconstructions of complex geometries supported by an online feedback method for user guidance during image acquisition. Our approach is suited for seamlessly matching and integrating images with different scales, from different view points (aerial and terrestrial), and with different cameras into one single reconstruction. We evaluate our approach based on different datasets for applications in mining, archaeology and urban environments and thus demonstrate the flexibility and high accuracy of our approach. Our evaluation includes accuracy related analyses investigating camera self-calibration, georegistration and camera network configuration.
AB - Abstract During the last decades photogrammetric computer vision systems have been well established in scientific and commercial applications. Recent developments in image-based 3D reconstruction systems have resulted in an easy way of creating realistic, visually appealing and accurate 3D models. We present a fully automated processing pipeline for metric and geo-accurate 3D reconstructions of complex geometries supported by an online feedback method for user guidance during image acquisition. Our approach is suited for seamlessly matching and integrating images with different scales, from different view points (aerial and terrestrial), and with different cameras into one single reconstruction. We evaluate our approach based on different datasets for applications in mining, archaeology and urban environments and thus demonstrate the flexibility and high accuracy of our approach. Our evaluation includes accuracy related analyses investigating camera self-calibration, georegistration and camera network configuration.
KW - Photogrammetric computer vision
KW - Unmanned aerial vehicles
KW - Image-based 3D reconstruction
KW - Mapping
KW - Camera calibration
KW - Image acquisition
KW - Online feedback
KW - Structure-from-motion
KW - Georeferencing
KW - Fiducial markers
KW - Accuracy evaluation
U2 - 10.1016/j.cviu.2016.04.008
DO - 10.1016/j.cviu.2016.04.008
M3 - Artikel
JO - Computer Vision and Image Understanding
JF - Computer Vision and Image Understanding
SN - 1077-3142
ER -