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Objective evaluation of light field rendering methods using effective sampling density

机译:使用有效采样密度客观评估光场渲染方法

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Light field rendering (LFR) is an active research area in computer vision and computer graphics. LFR plays a crucial role in free viewpoint video systems (FVV). Several rendering algorithms have been suggested for LFR. However, comparative evaluation of these methods is often limited to subjective assessment of the output. To overcome this problem, this paper presents a geometric measurement, Effective Sampling Density of the scene, referred to as effective sampling for brevity, for objective comparison and evaluation of LFR algorithms. We have derived the effective sampling for the well-known LFR methods. Both theoretical study and numerical simulation have shown that the proposed effective sampling is an effective indicator of the performance for LFR methods.
机译:光场渲染(LFR)是计算机视觉和计算机图形学的活跃研究领域。 LFR在自由视点视频系统(FVV)中起着至关重要的作用。对于LFR,已经提出了几种渲染算法。但是,这些方法的比较评估通常仅限于对输出进行主观评估。为了克服这个问题,本文提出了一种几何测量方法,即场景的有效采样密度,简称为有效采样,用于LFR算法的客观比较和评估。我们已经得出了众所周知的LFR方法的有效采样。理论研究和数值模拟均表明,所提出的有效采样是LFR方法性能的有效指标。

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