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Can we use smartphone-imaging sensors as low cost luminance mapping tools to support design processes, integrated lighting system control, and human factors research?

机译:我们可以使用智能手机成像传感器作为低成本亮度映射工具来支持设计过程,集成照明系统控制和人为因素研究吗?

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In this paper, High Dynamic Range (HDR) Photography methods (Inanici, 2006) are employed with both smartphone cameras and full-frame Complementary Metal-Oxide Semiconductor (CMOS) sensors to evaluate their accuracy in creating luminance maps and usefulness in practical applications. We answered three questions: can smartphone quality cameras function as inexpensive imaging sensors for HDR applications to collect scene luminance information accurate enough for use in: 1) human factors research, 2) building automation and control systems, and 3) teaching and learning scenarios? Three popular smartphones, the iPhone 5s, iPhone 6s, and Galaxy S6 Edge+ were chosen for comparison to the full-frame CMOS sensor found in the Canon EOS 5D, following current HDR best practices. In order to study each camera's absolute and relative accuracy across a wide brightness range we collected data within high, medium, and low luminance source scenes. We compared HDR luminance results captured by the iPhone 5s, iPhone 6s, and Galaxy S6 Edge+ in each scene with HDR luminance results captured using the Canon EOS 5D camera with a Sigma 8mm F3.5 EX DG fisheye lens, and also evaluated both against hand held measurements recorded using Minolta LS-110 and LS-160 luminance meters. When comparing luminance data collected with the smartphones to data collected using the Canon EOS 5D camera we found that the smaller CMOS sensors used in smartphones are more sensitive and tend to have more problems with luminance overflow (Jakubiec et al., 2016). Our findings suggest that smartphone cameras presently have severely limited value for use in human factors visual comfort research, especially when measuring the solar corona or sunlit surfaces, and for similar reasons should not be used to control automated blinds. The maximum luminance in a high brightness scene captured by the iPhone 6s is 13,790 cd/m~2 while the Galaxy S6 Edge+ captured a maximum of 51,580 cd/m~2, effectively capturing a mere 1.7% and 6.2% of the Canon EOS 5D's 825,300 cd/m~2 maximum respectively. However, these inexpensive cameras may hold potential for use in the control of electric lighting due to relatively lower luminance value ranges needed to adjust electric lighting. Smartphone cameras could also be used in basic teaching applications where the relative brightness of surfaces rather than absolute brightness is of interest.
机译:在本文中,高动态范围(HDR)摄影方法(Inanici,2006)与智能手机相机和全画幅互补金属氧化物半导体(CMOS)传感器一起使用,以评估其在创建亮度图时的准确性以及在实际应用中的实用性。我们回答了三个问题:智能手机品质的相机能否用作HDR应用的廉价成像传感器,以收集足够准确的场景亮度信息,以用于:1)人为因素研究,2)楼宇自动化和控制系统以及3)教学场景?根据目前的HDR最佳做法,选择了三款流行的智能手机iPhone 5s,iPhone 6s和Galaxy S6 Edge +与佳能EOS 5D中的全画幅CMOS传感器进行比较。为了研究在宽亮度范围内每个摄像机的绝对和相对精度,我们收集了高,中和低亮度源场景中的数据。我们将iPhone 5s,iPhone 6s和Galaxy S6 Edge +在每个场景中捕获的HDR亮度结果与使用佳能EOS 5D相机和Sigma 8mm F3.5 EX DG鱼眼镜头捕获的HDR亮度结果进行了比较,并针对手进行了评估使用Minolta LS-110和LS-160亮度计记录的保持测量值。将智能手机收集的亮度数据与佳能EOS 5D相机收集的数据进行比较时,我们发现智能手机中使用的较小的CMOS传感器更灵敏,并且在亮度溢出方面往往存在更多问题(Jakubiec等人,2016)。我们的发现表明,智能手机相机目前在用于人为因素视觉舒适性研究方面的价值非常有限,尤其是在测量日冕或阳光照射的表面时,并且出于类似原因,不应将其用于控制​​自动百叶窗。 iPhone 6s捕获的高亮度场景中的最大亮度为13,790 cd / m〜2,而Galaxy S6 Edge +捕获的最大亮度为51,580 cd / m〜2,实际上仅捕获了佳能EOS 5D的1.7%和6.2%。最大825,300 cd / m〜2然而,由于调节电子照明所需的相对较低的亮度值范围,这些廉价的照相机可能具有用于控制电子照明的潜力。智能手机相机也可以用在基本教学应用中,在这些应用中,需要关注表面的相对亮度而不是绝对亮度。

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