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.
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。
In the second chapter, we talk about the method for camera self-calibration through translation movement of the camera.
第二章主要给出通过摄像机的平移运动来实现自定标的方法。
The research of the thesis belongs to the field of ibr, and aims at applying camera self-calibration to ibr.
本文研究的内容属于IBR范畴，主要讨论把摄像机自定标技术应用到IBR中。
Secondly, a new method with scene constraint and the constraint of principal point for camera self-calibration based on the linear iteration is presented.
其次，提出了综合利用空间平行线约束和相机主点位置约束的线性迭代自定标方法，提高了相机自定标的鲁棒性。
In the end, we also give a brief review of self-calibration techniques under other camera models.
最后还简要介绍了几种非透视模型下的摄像机自标定方法。
There are generally two kinds of methods for camera calibration: normal camera calibration methods and self-calibration.
摄像机定标大体可以分为两种方法，即传统摄像机定标方法和摄像机的自定标方法。
And the self-calibration method of camera is to resolve the basic matrix with the geometrical relation amount many different images, so the internal and external parameters can be resolved.
摄像机自定标方法则是利用多幅不同的图像之间的几何关系，通过求解基本矩阵求得摄像机的内部参数和还原摄像机的外部参数。
This paper proposed a new camera self-calibration method based on image sequences, which combined the theory of photogrammetry and computer vision.
提出了一种新的结合摄影测量和计算机视觉相关理论的摄像机自标定方法。
In this paper, we discuss a new method for camera self-calibration based on a plane pattern of equilateral-dodecagon.
基于平面模板摄像机自标定的新算法，利用正六边形的特性，给出了一种精确求解其外接圆圆心的巧妙方法。
The main work of this thesis consists of the following three parts: 1. Camera Self-calibration Based on Circular Points.
主要工 作可以归纳为以下三个方面：1．基于圆环点的摄像机自标定方法研究。
The main work of this thesis consists of the following three parts: 1. Camera Self-calibration Based on Circular Points.
主要工 作可以归纳为以下三个方面：1．基于圆环点的摄像机自标定方法研究。
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