Open AccessLinear stratified approach using full geometric constraints for 3D scene reconstruction and camera calibration
Author(s) -
Jae-Hean Kim,
Bon-Ki Koo
Publication year - 2013
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.004456
Subject(s) - orthogonality , coplanarity , computer science , affine transformation , camera resectioning , computer vision , 3d reconstruction , artificial intelligence , metric (unit) , calibration , iterative reconstruction , algorithm , mathematics , geometry , operations management , statistics , economics
This paper presents a new linear framework to obtain 3D scene reconstruction and camera calibration simultaneously from uncalibrated images using scene geometry. Our strategy uses the constraints of parallelism, coplanarity, colinearity, and orthogonality. These constraints can be obtained in general man-made scenes frequently. This approach can give more stable results with fewer images and allow us to gain the results with only linear operations. In this paper, it is shown that all the geometric constraints used in the previous works performed independently up to now can be implemented easily in the proposed linear method. The study on the situations that cannot be dealt with by the previous approaches is also presented and it is shown that the proposed method being able to handle the cases is more flexible in use. The proposed method uses a stratified approach, in which affine reconstruction is performed first and then metric reconstruction. In this procedure, the additional constraints newly extracted in this paper have an important role for affine reconstruction in practical situations.