Evaluations on Multi-scale Camera Networks for Precise and Geo-accurate Reconstructions from Aerial and Terrestrial Images with User Guidance
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.
http://www.sciencedirect.com/science/article/pii/S1077314216300327
BibTeX
@article{Rumpler-2017-5495,author = {Markus Rumpler and Alexander Tscharf and Christian Mostegel and Shreyansh Daftry and Christof Hoppe and Rudolf Prettenthaler and Friedrich Fraundorfer and Gerhard Mayer and Horst Bischof},
title = {Evaluations on Multi-scale Camera Networks for Precise and Geo-accurate Reconstructions from Aerial and Terrestrial Images with User Guidance},
journal = {Computer Vision and Image Understanding},
year = {2017},
month = {April},
volume = {157},
pages = {255 - 273},
}