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Rectification Using Different Types of Cameras Attached to a Vehicle

机译:使用连接到车辆的不同类型的摄像机进行校正

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摘要

The rectification process is a compulsory step in stereo matching computation. To obtain depth information, stereo camera systems are often installed in vehicles for outdoor and street-related applications, including vehicle and pedestrian detection, lane detection, and traffic sign recognition. In this paper, we propose a rectification method that uses currently available front- and rear-view vehicle cameras to produce rectified stereo images. The proposed method can be employed with different types of cameras that have varying focal lengths. In addition, this method tolerates the problem of camera alignment variation from normal stereo camera systems. To achieve this, a compensation method for different focal lengths and the estimation of image relationships are introduced. The experimental results demonstrate that the proposed method can operate robustly and accurately with different kinds of stereo images and significantly outperforms a state-of-the-art rectification method.
机译:整流过程是立体匹配计算中的必修步骤。为了获得深度信息,通常在车辆中安装用于室外和街道相关应用的立体摄像头系统,包括车辆和行人检测,车道检测和交通标志识别。在本文中,我们提出了一种校正方法,该方法使用当前可用的前视和后视车辆摄像头来产生校正后的立体图像。所提出的方法可以用于具有不同焦距的不同类型的相机。另外,该方法容忍了与常规立体摄像机系统相比摄像机对准变化的问题。为此,引入了针对不同焦距的补偿方法和图像关系的估计。实验结果表明,该方法可以在不同种类的立体图像上稳定,准确地运行,并且明显优于最新的整流方法。

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