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A novel camera calibration technique based on differential evolution particle swarm optimization algorithm

Deng, L and Lu, G and Shao, Y and Fei, M and Hu, H (2016) 'A novel camera calibration technique based on differential evolution particle swarm optimization algorithm.' Neurocomputing, 174. 456 - 465. ISSN 0925-2312

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Abstract

© 2015 Elsevier B.V. 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.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 04 Sep 2015 14:03
Last Modified: 23 Jan 2019 00:18
URI: http://repository.essex.ac.uk/id/eprint/14775

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