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- W2049332309 abstract "The purpose of this research is to show how common computer vision techniques can be implemented in such a way that it is possible to automate the process of analytical photogram-metry. This work develops a workflow that generates a sparse three-dimensional point cloud from a bundle of images using SIFT, RANSAC, and a sparse bundle adjustment along with basic photogrammetric methods. It then goes on to show how the output of the sparse reconstruction method can be used to generate denser three-dimensional point clouds that can be facetized and turned into high resolution three-dimensional models. This workflow was successfully tested on a five image dataset taken with RIT's WASP imaging sensor over the Van Lare wastewater treatment plant in Rochester, NY." @default.
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- W2049332309 date "2010-11-01" @default.
- W2049332309 modified "2023-09-26" @default.
- W2049332309 title "Applying computer vision techniques to perform semi-automated analytical photogrammetry" @default.
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- W2049332309 doi "https://doi.org/10.1109/wnyipw.2010.5649777" @default.
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