文章基本信息

标题：Two New Algorithms to Retrieve the Calibration Matrix from the 3-D Projective Camera Model
本地全文：下载
作者：Gamal H. Seedahmed ; Ayman F. Habib
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 3 B
页码：241-244
出版社：Copernicus Publications
摘要：By relating the projective camera model to the perspective one, using homogenous coordinates representation, the interior orientation parameters constitute what is called the calibration matrix. This paper presents two new algorithms to retrieve the calibration matrix from the projective camera model. In both algorithms, a collective approach was adopted, using matrix factorization. The calibration matrix was retrieved from a quadratic matrix term. The two algorithms were framed around a correct utilization of Cholesky factorization to decompose the quadratic matrix term. The first algorithm used an iterative Cholesky factorization to retrieve the calibration matrix from the quadratic matrix term. The second algorithm used Cholesky factorization to factor the quadratic matrix term but after its inversion. The basic argument behind the two algorithms is that: the direct use of Cholesky factorization does not reveal the correct decomposition due to the missing matrix structure in terms of lower-upper order. In both algorithms, a successful retrieval of the calibration matrix was achieved. This paper explains the key ideas behind the two algorithms, accommodated with a simulated example to demonstrate their validity
关键词：DLT; Calibration Matrix; Cholesky Factorization