非线性模型下的摄像机自标定

摄像机标定是从二维图像获取三维信息必不可少的步骤，线性（小孔）模型摄像机自标定，目前已成为计算机视觉领域的研究热点之一，对于非线性模型下摄像机的自标定，目前还未见到相关的研究报道，用于线性模型一般不能准确地描述真实像机的几何成像关系，因此对非线性模型摄像机自标定的研究具有十分重要的实际意义，该文主要探索非线性模型摄像机的自标定方法，基本原理是将非线性模型视为线性模型和畸变项的叠加，然后利用线性模型的基本矩阵或单应矩阵，给出非线性模型参数的约束方程，从而实现非线性模型摄像机的自标定，模拟和真实图像实验均表明该文所给的方法是可行的，具有一定的实用价值。

Self-Calibration of a Camera with a Non-Linear Model

Camera calibration is an indispensable step to obtain 3D geometric information from 2D images. Self calibration of a camera with a linear model (hereafter called a linear camera) has become one of the major research directions in computer vision field. However, to our knowledge, there has been no reports in the literature on self calibrating a camera with a non linear model (hereafter called a non linear camera). Since a linear camera model cannot in general accurately represent the imaging geometry of a real camera, it is both necessary and important to explore ways of self calibrating a non linear camera. In this paper, a self calibration method of a non linear camera is proposed. The basic principle of the method is to model the non linear camera as a linear camera plus a non linear distortion part, then a set of non linear constraints on the non intrinsic parameters is derived by means of fundamental matrices or homographies associated with linear camera. Experiments with simulated data as well as with real images show that the proposed method is workable, and applicable in real applications.