基本矩阵(线性微分方程)
摄影测量学
射影几何
计算机科学
极线几何
投影(关系代数)
正投影
计算
代表(政治)
张量(固有定义)
域代数上的
钥匙(锁)
计算机视觉
人工智能
几何学
代数几何
数学
算法
图像(数学)
纯数学
数学分析
政治
法学
计算机安全
政治学
作者
Richard Hartley,Andrew Zisserman
标识
DOI:10.1017/cbo9780511811685
摘要
A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.
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