By providing angular and spatial information of light rays, light field images are widely used in many applications. To capture large field of view light field, existing approaches either stitch small field of view light fields, whose apertures are also small, or leverage specialized equipments, which are not accessible to ordinary users. In this paper, we present a method to extract fully 360° field of view panoramic light fields from densely sampled hand-held videos. Unlike previous works, our method handles the large exposure variation and motion blur problems, which are common in the panoramic capture and hand-held videos. To provide real-time rendering performance, our method applies light field sampling to the extracted panoramic light field. Based on the unstructured representation, our method can sample the light field without explicit parameterization. We formulate the sampling problem into a set multicover problem and solve it globally using integer linear programming. Compared with the greedy based method, our approach can use much less video frames to represent the panoramic light field, but still can get better rendering results.

中文翻译：

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手持视频全景光场及其采样实时渲染

通过提供光线的角度和空间信息，光场图像被广泛应用于许多应用中。为了捕捉大视场光场，现有的方法要么拼接孔径也很小的小视场光场，要么利用普通用户无法访问的专用设备。在本文中，我们提出了一种从密集采样的手持视频中提取完全 360° 视野全景光场的方法。与之前的工作不同，我们的方法处理了大曝光变化和运动模糊问题，这些问题在全景捕捉和手持视频中很常见。为了提供实时渲染性能，我们的方法将光场采样应用于提取的全景光场。基于非结构化表示，我们的方法可以在没有明确参数化的情况下对光场进行采样。我们将采样问题表述为一个集合多重覆盖问题，并使用整数线性规划全局解决它。与基于贪婪的方法相比，我们的方法可以使用更少的视频帧来表示全景光场，但仍然可以获得更好的渲染结果。