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A Novel Depth Recovery Approach from Multi-View Stereo Based Focusing

机译:一种从多视图基于立体声的聚焦的深度深度恢复方法

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In this paper, we propose a novel depth recovery method from multi-view stereo based focusing. Inspired by the 4D light field theory, we discover the relationship between classical multi-view stereo (MVS) and depth from focus (DFF) methods and concern about different frequency distribution in 2D light field space. Then we propose a way to separate the depth recovery into two steps. At the first stage, we choose some depth candidates using existing multi-view stereo method. At the second phase, the depth from focusing algorithm is employed to determine the final depth. As well known, multi-view stereo and depth from focus need different kinds of input images, which can not be acquired at the same time by using traditional imaging system. We have addressed this issue by using a camera array system and synthetic aperture photography. Both multi-view images and distinct defocus blur images can be captured at the same time. Experimental results have shown that our proposed method can take advantages of MVS and DFF and the recovered depth is better than traditional methods.
机译:在本文中,我们提出了从多视点立体基于聚焦的新的深度恢复方法。通过4D光场理论启发,我们发现经典多视点立体(MVS)和深度之间从焦点(DFF)的方法和关注在2D光场空间中的不同的频率分布的关系。然后,我们提出了一种深度恢复分成两个步骤。在第一阶段,我们使用现有的多视点立体方法选择一些深度的候选人。在第二阶段,从聚焦算法深度被用于确定最终深度。如从焦点需要不同种类的输入图像,其不能由使用传统成像系统的同时获取的公知的,多视点立体和深度。我们通过使用相机阵列系统和合成孔径摄影解决了这个问题。两个多视点图像和不同散焦模糊的图像可以在同一时间被捕获。实验结果表明,我们提出的方法可以采取MVS和DFF的优势和恢复深度优于传统方法。

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