In the previous chapter, we saw how 2D and 3D point sets could be aligned and how such alignments could be used to estimate both a camera's pose and its internal calibration parameters. In this chapter, we look at the converse problem of estimating the locations of 3D points from multiple images given only a sparse set of correspondences between image features. While this process often involves simultaneously estimating both 3D geometry (structure) and camera pose (motion), it is commonly known as structure from motion (Ullman 1979)
%0 Book Section
%1 2011-szeliski
%A Szeliski, Richard
%B Computer Vision: Algorithms and Applications
%C London
%D 2011
%I Springer London
%K computer from motion sfm structure vision
%P 303-334
%R 10.1007/978-1-84882-935-0_7
%T Structure from motion
%U https://doi.org/10.1007/978-1-84882-935-0_7
%X In the previous chapter, we saw how 2D and 3D point sets could be aligned and how such alignments could be used to estimate both a camera's pose and its internal calibration parameters. In this chapter, we look at the converse problem of estimating the locations of 3D points from multiple images given only a sparse set of correspondences between image features. While this process often involves simultaneously estimating both 3D geometry (structure) and camera pose (motion), it is commonly known as structure from motion (Ullman 1979)
%@ 978-1-84882-935-0
@inbook{2011-szeliski,
abstract = {In the previous chapter, we saw how 2D and 3D point sets could be aligned and how such alignments could be used to estimate both a camera's pose and its internal calibration parameters. In this chapter, we look at the converse problem of estimating the locations of 3D points from multiple images given only a sparse set of correspondences between image features. While this process often involves simultaneously estimating both 3D geometry (structure) and camera pose (motion), it is commonly known as structure from motion (Ullman 1979)},
added-at = {2021-07-05T15:17:41.000+0200},
address = {London},
author = {Szeliski, Richard},
biburl = {https://www.bibsonomy.org/bibtex/2ef5883457808459a470fc0bc62b9a3c7/pkoch},
booktitle = {Computer Vision: Algorithms and Applications},
doi = {10.1007/978-1-84882-935-0_7},
interhash = {17826af346ad77adf8ab0c3428258cbd},
intrahash = {ef5883457808459a470fc0bc62b9a3c7},
isbn = {978-1-84882-935-0},
keywords = {computer from motion sfm structure vision},
pages = {303-334},
publisher = {Springer London},
timestamp = {2021-07-05T15:17:51.000+0200},
title = {Structure from motion},
url = {https://doi.org/10.1007/978-1-84882-935-0_7},
year = 2011
}