Autonomous driving: a camera calibration method

b) Paper title, author's names and affiliation.



Title:

A Quadrant Approach of Camera Calibration Method for Depth Estimation Using a Stereo Vision System



Author’s names:

Oscar Real-Moreno

Julio C. Rodríguez-Quiñonez

Oleg Sergiyenko

Wendy Flores-Fuentes

Moises J. Castro-Toscano

Jesús E. Miranda-Vega

Paolo Mercorelli

Jorge Alejandro Valdez-Rodríguez

Gabriel Trujillo-Hernández

Jonathan J. Sanchez-Castro



Affiliation:

- Engineering Faculty, Universidad Autónoma de Baja California, Mexicali, Baja California, México

- Engineering Institute, Universidad Autónoma de Baja California, Mexicali, Baja California, México

- Department of Computer Systems, Tecnológico Nacional de México /IT Mexicali, Mexicali, Baja California, México

- Institute of Product and Process Innovation, Leuphana University of Lueneburg, Lueneburg, Germany



c) Paper 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.



d) Information about the video for the YouTube page

This video presents a camera calibration method for a stereo vision system. This system is designed to be merged with an object detection algorithm to perform spatial object detection for autonomous driving.