A Self-adaptive Bat Algorithm for Camera Calibration

DOI

10.2991/ameii-16.2016.241How to use a DOI?

Keywords

Camera calibration, Self-adaptive bat algorithm, Intrinsic parameters

Abstract

To obtain more accurate results of optimization calibration, an improved self-adaptive bat algorithm of camera calibration was proposed. Firstly, step parameters were set adaptively so that the objective function could avoid local minima. Secondly, the improved bat algorithms used in non-linear camera calibration did not need initial estimation values. So the proposed method could solve the problem that traditional optimization algorithms were sensitive to initial value. Furthermore, the self-adaptive bat algorithm combined with the process of camera calibration was used to optimize the camera's intrinsic parameters and the coefficient of radial distortion. Finally, the average re-projection error was analyzed, and the mean absolute error and the standard deviation were also calculated on the cases of different noise level. The experimental evaluation demonstrates that the proposed method was more efficient and accurate.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaozhi Liu
AU  - Didi Qi
PY  - 2016/04
DA  - 2016/04
TI  - A Self-adaptive Bat Algorithm for Camera Calibration
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.241
DO  - 10.2991/ameii-16.2016.241
ID  - Liu2016/04
ER  -