Abstract
An extreme learning machine (ELM) based camera calibration method is proposed for monocular vision system in this paper. Extreme learning machine is used to depict the relationship between the image space and the world space, in which any prior knowledge on camera model or parameters is not needed, and faster training speed and higher precision are gotten. The influence of environmental noise to the calibration precision can be effectively attenuated. The validity of the proposed method is proved by comparison with camera calibration based on BP algorithm.
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© 2013 Springer-Verlag Berlin Heidelberg
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Zhaohu, C., Xuemei, R., Qiang, C. (2013). Camera Calibration Based on Extreme Learning Machine. In: Yang, G. (eds) Proceedings of the 2012 International Conference on Communication, Electronics and Automation Engineering. Advances in Intelligent Systems and Computing, vol 181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31698-2_17
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DOI: https://doi.org/10.1007/978-3-642-31698-2_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31697-5
Online ISBN: 978-3-642-31698-2
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