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SCENE RECONSTRUCTION FROM HIGH SPATIO-ANGULAR RESOLUTION LIGHT FIELDS

机译:高空间角分辨光场的场景重建

摘要

The disclosure provides an approach for estimating depth in a scene. According to one aspect, regions where the depth estimation is expected to perform well may first be identified in full-resolution epipolar-plane images (EPIs) generated from a plurality of images of the scene. Depth estimates for EPI-pixels with high edge confidence are determined by testing a number of discrete depth hypotheses and picking depths that lead to highest color density of sampled EPI-pixels. The depth estimate may also be propagated throughout the EPIs. This process of depth estimation and propagation may be iterated until all EPI-pixels with high edge confidence have been processed, and all EPIs may also be processed in this manner. The EPIs are then iteratively downsampled to coarser resolutions, at which edge confidence for EPI-pixels not yet processed are determined, depth estimates of EPI-pixels with high edge confidence made, and depth estimates propagated throughout the EPIs.
机译:本公开提供了一种用于估计场景中的深度的方法。根据一个方面,可以首先在从场景的多个图像生成的全分辨率对极平面图像(EPI)中识别期望深度估计执行良好的区域。具有高边缘置信度的EPI像素的深度估计是通过测试导致采样的EPI像素的最高颜色密度的许多离散深度假设和拾取深度来确定的。深度估计也可以在整个EPI中传播。深度迭代和深度传播的过程可以重复进行,直到具有高边缘置信度的所有EPI像素都已被处理,并且所有EPI也可以以此方式进行处理。然后,将EPI迭代下采样到较高分辨率,在该分辨率下,确定尚未处理的EPI像素的边缘置信度,对具有高边缘置信度的EPI像素进行深度估计,并在整个EPI中传播深度估计。

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