Stochastic Light Field Holography
Stochastic Light Field Holography
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DOI：
10.1109/iccp56744.2023.10233716
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发表时间：
2023-07
期刊：
影响因子：
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通讯作者：
Florian Schiffers;Praneeth Chakravarthula;N. Matsuda;Grace Kuo;Ethan Tseng;Douglas Lanman;Felix Heide-Felix-Hei
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文献类型：
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作者：
Florian Schiffers;Praneeth Chakravarthula;N. Matsuda;Grace Kuo;Ethan Tseng;Douglas Lanman;Felix Heide-Felix-Hei
视觉图灵测试是评估全息显示真实感的最终目标。先前的研究重点是解决大焦距范围内有限光学扩展量和图像质量等挑战，但他们没有研究瞳孔采样对全 3D 全息图观看体验的影响。在这项工作中，我们通过一种新颖的全息图生成算法来解决这个问题，该算法的动机是匹配非相干（光场）和相干（维格纳函数）光传输的投影算子。为此，我们使用合成照片来监督全息图计算，这些照片是在优化过程中使用来自随机采样的光瞳状态的光场重新聚焦来即时渲染的。所提出的方法产生具有正确视差和焦点线索的全息图，这对于通过视觉图灵测试非常重要。我们验证了我们的方法与使用光场和焦点堆栈监督的最先进的 CGH 算法相比具有优势。我们的实验表明，我们的算法在各种不同的瞳孔状态下进行评估时改善了观看体验。
The Visual Turing Test is the ultimate goal to evaluate the realism of holographic displays. Previous studies have focused on addressing challenges such as limited étendue and image quality over a large focal volume, but they have not investigated the effect of pupil sampling on the viewing experience in full 3D holograms. In this work, we tackle this problem with a novel hologram generation algorithm motivated by matching the projection operators of incoherent (Light Field) and coherent (Wigner Function) light transport. To this end, we supervise hologram computation using synthesized photographs, which are rendered on-the-fly using Light Field refocusing from stochastically sampled pupil states during optimization. The proposed method produces holograms with correct parallax and focus cues, which are important for passing the Visual Turing Test. We validate that our approach compares favorably to state-of-the-art CGH algorithms that use Light Field and Focal Stack supervision. Our experiments demonstrate that our algorithm improves the viewing experience when evaluated under a large variety of different pupil states.