Camera Calibration with 1D Objects

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Author(s): José Alexandre de França (Universidade Estadual de Londrina, Brazil), Marcelo Ricardo Stemmer (Universidade Federal de Santa Catarina, Brazil), Maria B. de Morais França (Universidade Estadual de Londrina, Brazil)and Rodrigo H. Cunha Palácios (Universidade Tecnológica Federal do Paraná, Brazil)
Copyright: 2012
Pages: 21
Source title: Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
Source Author(s)/Editor(s): Vijay Kumar Mago (Simon Fraser University, Canada)and Nitin Bhatia (DAV College, India)
DOI: 10.4018/978-1-61350-429-1.ch005

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Camera calibration is a process that allows to fully understand how the camera forms the image. It is necessary especially when 3D information of the scene must be known. Calibration can be performed using a 1D pattern (points on a straight line). This kind of pattern has the advantage of being “visible” simultaneously even by cameras in opposite positions from each other. This makes the technique suitable for calibration of multiple cameras. Unfortunately, the calibration with 1D patterns often leads to poorly accurate results. In this work, the methods of single and multi-camera calibration are analyzed. It is shown that, in some cases, the accuracy of this type of algorithm can be significantly improved by simply performing a normalization of coordinates of the input points. Experiments on synthetic and real images are used to analyze the accuracy of the discussed methods.

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Camera Calibration with 1D Objects

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