Abstract
This paper introduces a Bayesian approach to solve the problem of fitting multiple straight lines to a set of 2D points. Other approaches use many arbitrary parameters and threshold values, the proposed criterion uses only the parameters of the measurement errors. Models with multiple lines are useful in many applications, this paper analyzes the performance of the new approach to solve a classical problem in robotics: finding a map of lines from laser measurements. Tests show that the Bayesian approach obtains reliable models.
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Acknowledgments
The authors would like to thank the anonymous reviewers and the editor for their constructive criticism and useful comments. The authors also like to thank Adan Hurtado for his assistance in preparing the final document.
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Research partially supported by CONACYT under project CATEDRAS-3163.
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Lara-Alvarez, C., Romero, L. & Gomez, C. Multiple straight-line fitting using a Bayes factor. Adv Data Anal Classif 11, 205–218 (2017). https://doi.org/10.1007/s11634-016-0236-z
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DOI: https://doi.org/10.1007/s11634-016-0236-z