Dynamic and Scalable Large Scale Image Reconstruction
Recent approaches to reconstructing city-sized areas from large image collections usually process them all at once and only produce disconnected descriptions of image subsets, which typically correspond to major landmarks. In contrast, we propose a framework that lets us take advantage of the available meta-data to build a single, consistent description from these potentially disconnected descriptions. Furthermore, this description can be incrementally updated and enriched as new images become avail- able. We demonstrate the power of our approach by building large-scale reconstructions using images of Lausanne and Prague.
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Strecha, C., Pylvanainen, T., & Fua, P. (2010). Dynamic and Scalable Large Scale Image Reconstruction. Proceedings of 23rd IEEE Conference on Computer Vision and Pattern Recognition, 406–413. https://doi.org/10.1109/CVPR.2010.5540184
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