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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,以支持设计过程,集成照明系统控制和人类因素研究吗?

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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帧互补金属氧化物半导体(CMOS)传感器一起使用,以评估它们在实际应用中创造亮度图和有用性方面的精度。我们回答了三个问题:智能手机质量相机功能可以作为HDR应用的廉价成像传感器,以便收集足够的场景亮度信息,可用于:1)人类因素研究,2)楼宇自动化和控制系统,以及3)教学和学习情景?选择三个流行的智能手机,iPhone 5S,iPhone 6s和Galaxy S6 Edge +与Canon EOS 5D中的全帧CMOS传感器进行比较,如今的HDR最佳实践。为了在宽亮度范围内研究每个相机的绝对和相对精度,我们在高,介质和低亮度源场景中收集数据。我们比较了iPhone 5s,iPhone 6s和Galaxy S6 Edge +在每个场景中捕获的HDR亮度结果,使用CANON EOS 5D摄像机使用带有Sigma 8MM F3.5 EX DG Fisheye镜头的HDR亮度结果,并且还针对手使用MINOLTA LS-110和LS-160亮度计记录的测量。在使用智能手机收集的亮度数据与使用佳能EOS 5D摄像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CMOS传感器更敏感,并且倾向于有亮度溢出的问题(Jakubiec等,2016)。我们的研究结果表明,智能手机摄像机目前对人类因素的使用具有严重限制的视觉舒适性研究,特别是在测量太阳能电晕或阳光表面时,并且由于类似原因,不应用于控制自动百叶窗。由iPhone 6S捕获的高亮度场景中的最大亮度为13,790cd / m〜2,而Galaxy S6 Edge +最多可捕获51,580cd / m〜2,有效捕获佳能EOS 5D的1.7%和6.2% 825,300cd / m〜2最大值。然而,由于需要调节电照明所需的相对较低的亮度值范围,这些廉价的摄像机可以保持用于控制电照的电势。智能手机相机也可以用于基本教学应用,其中表面的相对亮度而不是绝对亮度的感兴趣。

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