TY - GEN
T1 - Calibration of binocular vision sensor with large field-of-view based on two small planar targets
AU - Yan, Feng
AU - Liu, Zhen
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery
PY - 2018/2/24
Y1 - 2018/2/24
N2 - The current calibration methods for binocular vision sensor (BVS) with large field-of-view (FOV) require large scale targets, which are hard to be manufactured, inconvenient to be posed and with low accuracy. In view of the above problems, this paper presents a method for calibrating BVS with large FOV based on two small planar targets connected rigidly. Firstly, the two small planar targets are approached nearly to the BVS, and each camera shoots the small target corresponding to it respectively. Then, the location uncertainty of the image feature points of targets is determined. The location deviation of image feature points and the cameras intrinsic parameters are derived by non-linear optimization. Finally, according to the constraint that the relative position of the two planar targets is invariable, the optimal solution of the transformation matrix can be obtained by nonlinear optimization. Experiment verifies the effectiveness of the proposed method.
AB - The current calibration methods for binocular vision sensor (BVS) with large field-of-view (FOV) require large scale targets, which are hard to be manufactured, inconvenient to be posed and with low accuracy. In view of the above problems, this paper presents a method for calibrating BVS with large FOV based on two small planar targets connected rigidly. Firstly, the two small planar targets are approached nearly to the BVS, and each camera shoots the small target corresponding to it respectively. Then, the location uncertainty of the image feature points of targets is determined. The location deviation of image feature points and the cameras intrinsic parameters are derived by non-linear optimization. Finally, according to the constraint that the relative position of the two planar targets is invariable, the optimal solution of the transformation matrix can be obtained by nonlinear optimization. Experiment verifies the effectiveness of the proposed method.
KW - Binocular Vision Sensor
KW - Camera Calibration
KW - Large FOV
KW - Small target
KW - Uncertainty
UR - https://www.scopus.com/pages/publications/85047360122
U2 - 10.1145/3191442.3191470
DO - 10.1145/3191442.3191470
M3 - 会议稿件
AN - SCOPUS:85047360122
T3 - ACM International Conference Proceeding Series
SP - 152
EP - 156
BT - Proceedings of 2018 International Conference on Image and Graphics Processing, ICIGP 2018
PB - Association for Computing Machinery
T2 - 2018 International Conference on Image and Graphics Processing, ICIGP 2018
Y2 - 24 February 2018 through 26 February 2018
ER -