Initialization method for self-calibration using 2-views

被引:4
|
作者
Ha, JE
Kang, DJ
机构
[1] Tongmyong Univ Informat Technol, Dept Multimedia Engn, Pusan, South Korea
[2] Tongmyong Univ Informat Technol, Dept Mecatron Engn, Pusan, South Korea
关键词
self-calibration; camera calibration; 3D recovery; initialization;
D O I
10.1016/j.patcog.2004.05.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently, 3D structure recovery through self-calibration of camera has been actively researched. Traditional calibration algorithm requires known 3D coordinates of the control points while self-calibration only requires the corresponding points of images, thus it has more flexibility in real application. In general, self-calibration algorithm results in the nonlinear optimization problem using constraints from the intrinsic parameters of the camera. Thus, it requires initial value for the nonlinear minimization. Traditional approaches get the initial values assuming they have the same intrinsic parameters while they are dealing with the situation where the intrinsic parameters of the camera may change. In this paper, we propose new initialization method using the minimum 2 images. Proposed method is based on the assumption that the least violation of the camera's intrinsic parameter gives more stable initial value. Synthetic and real experiment shows this result. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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页码:143 / 150
页数:8
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