Stereo Camera Calibration For Autonomous Car Applications

2022 2nd International Seminar on Machine Learning, Optimization, and Data Science (ISMODE) Pub Date : 2022-12-22 DOI:10.1109/ISMODE56940.2022.10180933

Muhammad Abdillah Rahmat, Indrabayu, A. Achmad, Ejah Umraeni Salam, Muhammad Fadhil Bin Bahrunnida

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Abstract

Several stages will be carried out in developing an intelligent transportation system, including building stereo vision by utilizing two cameras with stereo performance. Before vehicle object detection, vehicle distance and speed detection are implemented in the user’s vehicle by using cameras. Camera calibration is a process that should be noticed in computer vision. The calibration process is usually carried out if the camera is to be used to estimate the camera’s distance to a particular object. The camera stereo calibration system has been carried out and successfully implemented to detect vehicle distance and relative speed of vehicles on autonomous cars. OpenCV with c920 stRealm pro and c922 stRealm pro cameras is used to implement stereo vision on the camera. Optimal calibration conditions were obtained on a chessboard pattern measuring 3 cm with a distance between the lenses of 9.8 cm and shooting ranges from 0.5 cm. The optimal conditions were obtained based on the RMSE value of 0.4932.

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用于自动驾驶汽车的立体摄像头校准

智能交通系统的开发将分为几个阶段，包括利用具有立体性能的两个摄像头构建立体视觉。在车辆目标检测之前，通过摄像头在用户车辆中实现车辆距离和速度检测。摄像机标定是计算机视觉中需要注意的一个过程。如果相机要用于估计相机到特定物体的距离，则通常进行校准过程。摄像机立体标定系统已经成功实现，用于自动驾驶汽车的车辆距离和相对速度检测。OpenCV与c920流pro和c922流pro相机被用来实现相机上的立体视觉。在一个尺寸为3 cm、镜头间距为9.8 cm、射击距离为0.5 cm的棋盘图案上，获得了最佳校准条件。在RMSE值为0.4932的条件下，得到了最佳条件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2022 2nd International Seminar on Machine Learning, Optimization, and Data Science (ISMODE)

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