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Publication in BibTeX Format

@ARTICLE{AICPub836:1981, AUTHOR={Fischler, Martin A. and Bolles, Robert C.}, TITLE={Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography}, JOURNAL={Communications of the ACM}, PAGES={381-395}, NUMBER={6}, VOLUME={24}, YEAR={1981}, ABSTRACT={A new paradigm, Random Sample Consensus (RANSAC), for fitting a model to experimental data is introduced. RANSAC is capable of interpreting/smoothing data containing a significant percentage of gross errors, and is thus ideally suited for applications in automated image analysis where interpretation is based on the data provided by error-prone feature detectors. A major portion of this paper describes the application of RANSAC to the Location Determination Problem (LDP): Given an image depicting a set of landmarks with know locations, determine that point in space from which the image was obtained. In response to a RANSAC requirement, new results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form. These results provide the basis for an automatic system that can solve the LDP under difficult viewing.} }

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