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Proceedings Paper

A novel approach for camera self-calibration from projective reconstruction
Author(s): Haiyan Yu; Xiaolin Qiao; Jingyan Wang; Haobo Yu
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Paper Abstract

A novel approach for camera self-calibration is addressed in this paper. It is well known that one of problems for camera self-calibration is the matrix of the dual image of absolute conic (DIAC) is must positive definite. Then calibration matrix can be gotten by cholesky factorization from DIAC. In this paper, calibration matrix is directly optimized with nonlinear method which means that the solution of DIAC matrix is not necessary. It can help us avoid the positive definite problem. The algorithm builds on the basement of projective reconstruction, and it includes two steps. Firstly, the initial value of calibration matrix can be estimated from the manufacture explanation, then initial guess of infinity plane vector is searched out. Secondly, 8 parameters containing calibration matrix and infinity plane vector are optimized with Levenberg-Marquardt algorithm. Experiments validate the method.

Paper Details

Date Published: 8 August 2007
PDF: 8 pages
Proc. SPIE 6753, Geoinformatics 2007: Geospatial Information Science, 67532H (8 August 2007); doi: 10.1117/12.763534
Show Author Affiliations
Haiyan Yu, Harbin Institute of Technology (China)
Xiaolin Qiao, Harbin Institute of Technology (China)
Jingyan Wang, Petrochina Daqing Oilfield Co. Ltd. (China)
Haobo Yu, Petrochina Daqing Oilfield Co. Ltd. (China)

Published in SPIE Proceedings Vol. 6753:
Geoinformatics 2007: Geospatial Information Science
Jingming Chen; Yingxia Pu, Editor(s)

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