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Random sample consensus

Martin A. Fischler; Robert C. Bolles · Communications of the ACM · 1981

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Author / responsible party
Martin A. Fischler; Robert C. Bolles
Publisher
Communications of the ACM
Year
1981
Language
English

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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 known 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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APA 7

Fischler, M. A. & Bolles, R. C. (1981). Random sample consensus. https://doi.org/10.1145/358669.358692

MLA

Fischler, Martin A, and Robert C. Bolles. "Random sample consensus." 1981. https://doi.org/10.1145/358669.358692.

Chicago

Fischler, Martin A. and Robert C. Bolles. 1981. "Random sample consensus.". https://doi.org/10.1145/358669.358692.

Harvard

Fischler, M. A. and Bolles, R. C. 1981, Random sample consensus, Communications of the ACM, available at: https://doi.org/10.1145/358669.358692 [Accessed 8 Aug. 2026].

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Resource details

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Title
Random sample consensus
Author / contributors
Martin A. Fischler; Robert C. Bolles
Publisher
Communications of the ACM
Publication year
1981
Language
English

Subjects

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RANSAC; Smoothing; Computer science; Artificial intelligence; Landmark; Sample (material); Feature (linguistics); Computer vision; Set (abstract data type); Basis (linear algebra); Image (mathematics); Point (geometry)
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