Jeon Minkyung, Park Jinhong, Kim Jin-Woo, Woo Sungmin
Department of Information and Communication Engineering, Korea University of Technology and Education (KOREATECH), Cheonan-si 31253, Republic of Korea.
R&D Center, VisioNext, Seongnam-si 13488, Republic of Korea.
Sensors (Basel). 2024 Sep 20;24(18):6100. doi: 10.3390/s24186100.
In this study, we propose a novel rectification method for three cameras using a single image for depth estimation. Stereo rectification serves as a fundamental preprocessing step for disparity estimation in stereoscopic cameras. However, off-the-shelf depth cameras often include an additional RGB camera for creating 3D point clouds. Existing rectification methods only align two cameras, necessitating an additional rectification and remapping process to align the third camera. Moreover, these methods require multiple reference checkerboard images for calibration and aim to minimize alignment errors, but often result in rotated images when there is significant misalignment between two cameras. In contrast, the proposed method simultaneously rectifies three cameras in a single shot without unnecessary rotation. To achieve this, we designed a lab environment with checkerboard settings and obtained multiple sample images from the cameras. The optimization function, designed specifically for rectification in stereo matching, enables the simultaneous alignment of all three cameras while ensuring performance comparable to traditional methods. Experimental results with real camera samples demonstrate the benefits of the proposed method and provide a detailed analysis of unnecessary rotations in the rectified images.
在本研究中，我们提出了一种新颖的使用单幅图像进行深度估计的三相机校正方法。立体校正作为立体相机视差估计的基本预处理步骤。然而，现成的深度相机通常还包括一个额外的RGB相机用于创建3D点云。现有的校正方法仅对齐两个相机，需要额外的校正和重映射过程来对齐第三个相机。此外，这些方法需要多个参考棋盘格图像进行校准，并旨在最小化对齐误差，但当两个相机之间存在明显未对齐时，常常会导致图像旋转。相比之下，所提出的方法能够在单次拍摄中同时校正三个相机，而不会产生不必要的旋转。为实现这一点，我们设计了一个带有棋盘格设置的实验室环境，并从相机获取了多个样本图像。专门为立体匹配中的校正设计的优化函数，能够在确保性能与传统方法相当的同时，实现所有三个相机的同时对齐。使用真实相机样本的实验结果证明了所提出方法的优势，并对校正后图像中的不必要旋转进行了详细分析。
