DocumentCode
2549413
Title
Epipolar parameterization for reconstructing a 3D rigid curve
Author
Zhao, Changsheng ; Mohr, Roger
Author_Institution
LIFIA-INRI, Grenoble, France
fYear
1995
fDate
21-23 Nov 1995
Firstpage
67
Lastpage
72
Abstract
This paper describes a new method for reconstructing a 3D rigid curve from a sequence of uncalibrated images using 3D epipolar parameterization of an object. The approach can be divided into the following two parts: First, a nonlinear discrete method is presented for point by point reconstruction of the curve instead of whole curve reconstruction. Projective and Euclidean geometric tools are used. Second the parametric representation of the curve is defined by 3D B-spline curves, a linear method is proposed to interpolate the reconstructed points to obtain a complete curve. Thus it is proved that the 3D curve interpolation is equivalent to determining a set of control points of 3D regularized B-spline curves. It is shown that the 3D epipolar parameterization is an efficient method for reconstructing a 3D curve from image sequences. Experimental results are presented for real data
Keywords
computer vision; curve fitting; image reconstruction; image sequences; splines (mathematics); 3D B-spline curves; 3D curve interpolation; 3D epipolar parameterization; 3D rigid curve; Euclidean geometric tools; computer vision; control points; curve reconstruction; epipolar parameterization; image sequences; nonlinear discrete method; point by point reconstruction; projective geometric tools; robust surface descriptions; uncalibrated images; Calibration; Cameras; Computer vision; Image reconstruction; Image sequences; Layout; Robustness; Shape; Spline; Surface reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 1995. Proceedings., International Symposium on
Conference_Location
Coral Gables, FL
Print_ISBN
0-8186-7190-4
Type
conf
DOI
10.1109/ISCV.1995.476979
Filename
476979
Link To Document