A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2022. (IECON Proceedings (Industrial Electronics Conference)).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System
AU - Real-Moreno, Oscar
AU - Rodriguez-Quinonez, Julio C.
AU - Sergiyenko, Oleg
AU - Flores-Fuentes, Wendy
AU - Castro-Toscano, Moises J.
AU - Miranda-Vega, Jesus E.
AU - Mercorelli, Paolo
AU - Valdez-Rodriguez, Jorge Alejandro
AU - Trujillo-Hernandez, Gabriel
AU - Sanchez-Castro, Jonathan J.
N1 - Conference code: 48
PY - 2022/10/17
Y1 - 2022/10/17
N2 - Stereo vision systems are well know depth estimation methods with a large number of applications such as automatic inspection, autonomous navigation, process control, etc. The functioning principle of these systems is the triangulation between the real-world surface point and its respective projections on the image planes of each camera. One of the key points in order to obtain accurate measurements on stereo vision systems are the calibration of extrinsic and intrinsic parameters. This is why the work of this paper focuses on a camera calibration method to correct the error generated by the lens distortion. The proposed method divides the image in quadrants and generates an equation for each quadrant to correct the error generated by the lens distortion. The performed experiment demonstrated an accuracy improvement using the calibration method compared to the measures taken without a calibration method.
AB - Stereo vision systems are well know depth estimation methods with a large number of applications such as automatic inspection, autonomous navigation, process control, etc. The functioning principle of these systems is the triangulation between the real-world surface point and its respective projections on the image planes of each camera. One of the key points in order to obtain accurate measurements on stereo vision systems are the calibration of extrinsic and intrinsic parameters. This is why the work of this paper focuses on a camera calibration method to correct the error generated by the lens distortion. The proposed method divides the image in quadrants and generates an equation for each quadrant to correct the error generated by the lens distortion. The performed experiment demonstrated an accuracy improvement using the calibration method compared to the measures taken without a calibration method.
KW - depth estimation
KW - Lens distortion
KW - pattern match
KW - Stereo vision system
KW - triangulation
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85143895853&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/1fc09f61-96fe-3195-9007-2aabc221ac61/
U2 - 10.1109/IECON49645.2022.9968346
DO - 10.1109/IECON49645.2022.9968346
M3 - Article in conference proceedings
AN - SCOPUS:85143895853
SN - 978-1-6654-8026-0
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
CY - Piscataway
T2 - Conference - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Y2 - 17 October 2022 through 20 October 2022
ER -