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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

Standard

A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System. / Real-Moreno, Oscar; Rodriguez-Quinonez, Julio C.; Sergiyenko, Oleg et al.
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

Harvard

Real-Moreno, O, Rodriguez-Quinonez, JC, Sergiyenko, O, Flores-Fuentes, W, Castro-Toscano, MJ, Miranda-Vega, JE, Mercorelli, P, Valdez-Rodriguez, JA, Trujillo-Hernandez, G & Sanchez-Castro, JJ 2022, A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System. in IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), IEEE - Institute of Electrical and Electronics Engineers Inc., Piscataway, Conference - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022, Brussels, Belgium, 17.10.22. https://doi.org/10.1109/IECON49645.2022.9968346

APA

Real-Moreno, O., Rodriguez-Quinonez, J. C., Sergiyenko, O., Flores-Fuentes, W., Castro-Toscano, M. J., Miranda-Vega, J. E., Mercorelli, P., Valdez-Rodriguez, J. A., Trujillo-Hernandez, G., & Sanchez-Castro, J. J. (2022). A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System. In IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference)). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON49645.2022.9968346

Vancouver

Real-Moreno O, Rodriguez-Quinonez JC, Sergiyenko O, Flores-Fuentes W, Castro-Toscano MJ, Miranda-Vega JE et al. A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System. In 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)). doi: 10.1109/IECON49645.2022.9968346

Bibtex

@inbook{730032e217ee4bf8b096eb41d7f2bc65,
title = "A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System",
abstract = "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.",
keywords = "depth estimation, Lens distortion, pattern match, Stereo vision system, triangulation, Engineering",
author = "Oscar Real-Moreno and Rodriguez-Quinonez, {Julio C.} and Oleg Sergiyenko and Wendy Flores-Fuentes and Castro-Toscano, {Moises J.} and Miranda-Vega, {Jesus E.} and Paolo Mercorelli and Valdez-Rodriguez, {Jorge Alejandro} and Gabriel Trujillo-Hernandez and Sanchez-Castro, {Jonathan J.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; Conference - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 ; Conference date: 17-10-2022 Through 20-10-2022",
year = "2022",
month = oct,
day = "17",
doi = "10.1109/IECON49645.2022.9968346",
language = "English",
isbn = "978-1-6654-8026-0",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society",
address = "United States",
url = "https://iecon2022.org",

}

RIS

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 -

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Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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