摄像机自标定方法的研究与进展

被引:134
作者
孟晓桥
胡占义
机构
[1] 中国科学院自动化研究所模式识别国家重点实验室
关键词
摄像机自标定; 小孔模型; 无穷远平面; 绝对二次曲线(曲面);
D O I
10.16383/j.aas.2003.01.015
中图分类号
TP391.4 [模式识别与装置];
学科分类号
0811 ; 081101 ; 081104 ; 1405 ;
摘要
该文回顾了近几年来摄像机自标定技术的发展 ,并分类介绍了其中几种主要方法 .同传统标定方法相比 ,自标定方法不需要使用标定块 ,仅根据图像间图像点的对应关系就能估计出摄像机内参数 .文中重点介绍了透视模型下的几种重要的自标定方法 ,包括内参数恒定和内参数可变两种情形 ;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 .
引用
收藏
页码:110 / 124
页数:15
相关论文
共 8 条
  • [1] Sequential updating of projective and affine structure from motion
    Beardsley, PA
    Zisserman, A
    Murray, DW
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1997, 23 (03) : 235 - 259
  • [2] The development and comparison of robust methods for estimating the Fundamental Matrix
    Torr, PHS
    Murray, DW
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1997, 24 (03) : 271 - 300
  • [3] Self-calibration of stationary cameras
    Hartley, RI
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1997, 22 (01) : 5 - 23
  • [4] A THEORY OF SELF-CALIBRATION OF A MOVING CAMERA
    MAYBANK, SJ
    FAUGERAS, OD
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1992, 8 (02) : 123 - 151
  • [5] Shape and motion from image streams under orthography: a factorization method[J] . Carlo Tomasi,Takeo Kanade.International Journal of Computer Vision . 1992 (2)
  • [6] Self-calibration from the absolute conic on the plane at infinity .2 Pollefeys M,Van Gool L. In: Proceedings of Computer Analysis of Images and Patterns, Lecture Notes in Computer Science, Spring-Verlag . 1997
  • [7] Matrix Fondamentale et Calibration Visuelle Surl’en Vironnement[Ph D thesis] .2 Luong Q-T. . 1992
  • [8] Factorization methods for projective structure and motion .2 Triggs B. In: Proceedings of Computer Vision and Pattern Recognition,CA: San Francisco . 1996