Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
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DOI：
10.1017/cbo9780511811685.009
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发表时间：
2001-04
期刊：
影响因子：
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通讯作者：
Richard Hartley;Andrew Zisserman
中科院分区：
文献类型：
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作者：
Richard Hartley;Andrew Zisserman
概述本书的这一部分集中在单个透视摄像机的几何形状上，其中包含三章。映射点是一个3×4的矩阵P，它是从3个空间的世界点的均匀坐标到图像平面上成像点的均匀坐标的。可以从3×3矩阵K中包装，尤其是从中提取摄像机的性能，例如其中心和焦距。 p简单的分解。有两个特别重要的相机矩阵：有限的摄像机，以及其无限摄像头，例如代表平行投影的仿射相机描述摄像机矩阵P的估计，给定一组相应的世界和图像点的坐标8首先有三个主要主题。
Outline This part of the book concentrates on the geometry of a single perspective camera. It contains three chapters. Chapter 6 describes the projection of 3D scene space onto a 2D image plane. The camera mapping is represented by a matrix, and in the case of mapping points it is a 3 × 4 matrix P which maps from homogeneous coordinates of a world point in 3-space to homogeneous coordinates of the imaged point on the image plane. This matrix has in general 11 degrees of freedom, and the properties of the camera, such as its centre and focal length, may be extracted from it. In particular the internal camera parameters, such as the focal length and aspect ratio, are packaged in a 3 × 3 matrix K which is obtained from P by a simple decomposition. There are two particularly important classes of camera matrix: finite cameras, and cameras with their centre at infinity such as the affine camera which represents parallel projection. Chapter 7 describes the estimation of the camera matrix P, given the coordinates of a set of corresponding world and image points. The chapter also describes how constraints on the camera may be efficiently incorporated into the estimation, and a method of correcting for radial lens distortion. Chapter 8 has three main topics. First, it covers the action of a camera on geometric objects other than finite points.