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Conference Paper Linear Stratified Approach for 3D Modelling and Calibration using Full Geometric Constraints
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Authors
Kim Jae Hean
Issue Date
200906
Source
Conference on Computer Vision and Pattern Recognition (CVPR) 2009, pp.2144-2151
Publisher
IEEE
DOI
https://dx.doi.org/10.1109/CVPRW.2009.5206593
Project Code
09MS3500, Development of Full 3D Reconstruction Technology for Broadcasting Communication Fusion, Koo Bonki
Abstract
There have been many approaches to obtain 3D modeling and camera calibration simultaneously from uncalibrated images using parallelism, orthogonality and selfcalibration constraints. These approaches can give more stable results with fewer images and allow us to gain the results with only linear operations in most cases. It has been proved that the estimation results are accurate enough to be used as the initial values for nonlinear optimization to refine the results. In this paper, it is shown that all the linear constraints used in the previous works performed independently up to now can be implemented easily in the proposed linear method. 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. The study on the situations that can not be dealt with by the previous approaches is presented and it is shown that the proposed method being able to handle the cases is more flexible in use. © 2009 IEEE.
KSP Keywords
3D Modeling, 3D Modelling, Camera Calibration, Geometric constraints, Initial value, Linear constraints, Linear method, Nonlinear optimization, linear operations