TY - GEN
T1 - Initialization method for the self-calibration using minimal two images
AU - Ha, Jong Eun
AU - Kang, Dong Joong
PY - 2004
Y1 - 2004
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/77949672038
U2 - 10.1007/978-3-540-24768-5_98
DO - 10.1007/978-3-540-24768-5_98
M3 - Conference contribution
AN - SCOPUS:77949672038
SN - 3540220607
SN - 9783540220602
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 915
EP - 923
BT - Computational Science and Its Applications - ICCSA 2004 - International Conference, Proceedings
PB - Springer Verlag
T2 - International Conference on Computational Science and Its Applications, ICCSA 2004
Y2 - 14 May 2004 through 17 May 2004
ER -