期刊
NEUROCOMPUTING
卷 174, 期 -, 页码 456-465出版社
ELSEVIER
DOI: 10.1016/j.neucom.2015.03.119
关键词
Camera calibration; Internal parameter; External parameter; Differential evolution; Particle swarm algorithm; Visual identification
资金
- Key Project of Science and Technology Commission of Shanghai Municipality [14JC1402200]
- National Key Scientific Instrument and Equipment Development Project [2012YQ15008703]
- Fundamental research project of Shanghai Municipal Science and Technology Commission [12JC1404201]
- Shanghai College Young Teachers' Training Plan [B37010913003]
- Project of Partial Discharge Fault Source Location Visualization Research [D11010913033]
- State Grid Shanghai Municipal Electric Power Company
Camera calibration is one of the fundamental issues in computer vision and aims at determining the intrinsic and exterior camera parameters by using image features and the corresponding 3D features. This paper proposes a relationship model for camera calibration in which the geometric parameter and the lens distortion effect of camera are taken into account in order to unify the world coordinate system (WCS), the camera coordinate system (CCS) and the image coordinate system (ICS). Differential evolution is combined with particle swarm optimization algorithm to calibrate the camera parameters effectively. Experimental results show that the proposed algorithm has a good optimization ability to avoid local optimum and can complete the visual identification tasks accurately. (C) 2015 Elsevier B.V. All rights reserved.
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