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3D reconstruction based on light field images

机译：基于光场图像的3D重建

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This paper proposed a method of reconstructing three-dimensional(3D) scene from two light field images capture by Lytro illium. The work was carried out by first extracting the sub-aperture images from light field images and using the scale-invariant feature transform (SIFT) for feature registration on the selected sub-aperture images. Structure from motion (SFM) algorithm is further used on the registration completed sub-aperture images to reconstruct the three-dimensional scene. 3D sparse point cloud was obtained in the end. The method shows that the 3D reconstruction can be implemented by only two light field camera captures, rather than at least a dozen times captures by traditional cameras. This can effectively solve the time-consuming, laborious issues for 3D reconstruction based on traditional digital cameras, to achieve a more rapid, convenient and accurate reconstruction.
机译：提出了一种从Lytro illium捕获的两个光场图像中重建三维（3D）场景的方法。首先从光场图像中提取子孔径图像，然后使用尺度不变特征变换（SIFT）对所选子孔径图像进行特征配准，从而完成了这项工作。从运动构造（SFM）算法进一步用于配准完成的子孔径图像，以重建三维场景。最后获得了3D稀疏点云。该方法显示3D重建只能通过两次光场相机捕获来实现，而不是传统相机的至少十二次捕获。这样可以有效解决基于传统数码相机的3D重建过程中费时费力的问题，从而实现更快，方便，准确的重建。

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