论文标题
基于相对姿势估计的光场矫正
Light field Rectification based on relative pose estimation
论文作者
论文摘要
手持光场（LF）摄像机在计算机视觉中具有独特的优势，例如3D场景重建和深度估计。但是，相关应用程序受到超小基线的限制，例如，导致重建深度分辨率极低。为了解决这个问题，我们建议纠正LF以获得较大的基线。具体而言，所提出的方法将两个由两个手持式LF摄像机捕获的LF与随机相对姿势捕获，并提取相应的行相位的子孔径图像（SAI）以获得具有较大基线的LF。为了进行准确的整流，还提出了一种姿势估计方法，其中估算了两个LF相机之间的相对旋转和翻译。提出的姿势估计最小化了LF-Point-LF点对应模型中的自由度（DOF），并以线性方式明确解决了该模型。提出的姿势估计通过提供更准确的结果来支持纠正来优于最新算法。 3D重建的深度分辨率显着改善，证明了拟议的LF整流的有效性。
Hand-held light field (LF) cameras have unique advantages in computer vision such as 3D scene reconstruction and depth estimation. However, the related applications are limited by the ultra-small baseline, e.g., leading to the extremely low depth resolution in reconstruction. To solve this problem, we propose to rectify LF to obtain a large baseline. Specifically, the proposed method aligns two LFs captured by two hand-held LF cameras with a random relative pose, and extracts the corresponding row-aligned sub-aperture images (SAIs) to obtain an LF with a large baseline. For an accurate rectification, a method for pose estimation is also proposed, where the relative rotation and translation between the two LF cameras are estimated. The proposed pose estimation minimizes the degree of freedom (DoF) in the LF-point-LF-point correspondence model and explicitly solves this model in a linear way. The proposed pose estimation outperforms the state-of-the-art algorithms by providing more accurate results to support rectification. The significantly improved depth resolution in 3D reconstruction demonstrates the effectiveness of the proposed LF rectification.
