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Luminance-Based Measures of Shape and Detail Distinctness of 3D Objects as Important Predictors of Light Modeling Concept. Results of a Full-Scale Study Pairing Proposed Measures with Subjective Responses

机译:基于亮度的3D对象形状和细节区别的度量,作为光建模概念的重要预测指标。全面研究的结果与主观反应相结合的拟议措施

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Nowadays it is very common to discuss the various aspects of lighting within a framework of energy efficiency. In addition, the questions concerning lighting quality and occupants' comfort are another topic for active studies and debates. In the current investigation we tested one aspect of lighting quality-that is, light modeling-with the help of a luminance mapping technique. Here the degree of a 3D object's shape and detail distinctness are associated with modeling quality; that is, directly related to the light modeling concept. The aim of the study was to comprehend whether luminance-based design as a method, most perception oriented among others, could be applicable for the evaluation and prediction of the visibility of the shape and details of real 3D objects observed by people under daylight conditions and, further, to suggest luminance-based measures that can be developed into indicators of shape and details distinctness. Ordinal regression analysis of the survey results paired with several measures based on luminance values was performed. The tested measures were luminance ratio, mean luminance of the object, standard deviation of the luminances of the object, and the ratio between the highest luminance value of the object and mean luminance of the object. Among all of these measures the first three have the strongest correlations with subjective perception of 3D objects' shape and detail distinctness.
机译:如今,在能效框架内讨论照明的各个方面非常普遍。此外,有关照明质量和乘员舒适度的问题是积极研究和辩论的另一个主题。在当前的调查中,我们借助亮度映射技术测试了照明质量的一个方面,即光建模。在这里,3D对象的形状和细节的鲜明程度与建模质量相关;也就是说,与灯光建模概念直接相关。该研究的目的是理解基于亮度的设计作为一种方法(尤其是面向感知的方法)是否可用于评估和预测人们在日光条件下观察到的真实3D物体的形状和细节的可见性。 ,进一步建议可以将基于亮度的度量发展为形状和细节差异性的指标。对调查结果进行了序数回归分析,并结合了基于亮度值的几种度量。测试的度量是亮度比,物体的平均亮度,物体的亮度的标准偏差,以及物体的最高亮度值与物体的平均亮度之间的比率。在所有这些措施中,前三个与主观感知3D对象的形状和细节清晰度的相关性最强。

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