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Improved Depth Estimation with the Light Field Camera

机译:利用光场相机改进的深度估计

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Light-field cameras are used in consumer and industrial applications. An array of micro-lenses captures enough information that one can refocus images after acquisition, as well as shift one's viewpoint within the sub-apertures of the main lens, effectively obtaining multiple views. Thus, depth estimation from both defocus and correspondence are now available in a single capture. And Lytro.Inc also provides a depth estimation from a single-shot capture with light field camera, like Lytro Ilium. This Lytro depth estimation containing many correct depth information can be used for higher quality estimation. In this paper, we present a novel simple and principled algorithm that computes dense depth estimation by combining defocus, correspondence and Lytro depth estimations. We analyze 2D epipolar image (EPI) to get defocus and correspondence depth maps. Defocus depth is obtained by computing the spatial gradient after angular integration and correspondence depth by computing the angular variance from EPIs. Lytro depth can be extracted from Lyrto Ilium with software. We then show how to combine the three cues into a high quality depth map. Our method for depth estimation is suitable for computer vision applications such as matting, full control of depth-of-field, and surface reconstruction, as well as light filed display.
机译:光场相机用于消费和工业应用。一系列微透镜可捕获足够的信息,以使人们可以在采集后重新聚焦图像,以及在主透镜的子孔径内移动视点,从而有效地获得多个视图。因此,现在可以在一次捕获中使用散焦和对应关系进行深度估计。 Lytro.Inc还可以通过使用光场相机(如Lytro Ilium)进行单次拍摄来提供深度估计。包含许多正确深度信息的Lytro深度估算可用于更高质量的估算。在本文中,我们提出了一种新颖而简单的算法,该算法通过结合散焦,对应关系和Lytro深度估计来计算密集深度估计。我们分析2D对极图像(EPI)以获得散焦和对应的深度图。散焦深度是通过计算角度积分后的空间梯度而获得的,而散焦深度是通过根据EPI计算角度方差而得出的对应深度。可以使用软件从Lyrto Ilium提取Lytro深度。然后,我们展示如何将这三个线索组合成一个高质量的深度图。我们的深度估算方法适用于计算机视觉应用,例如消光,景深的完全控制,表面重建以及光场显示。

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