TY - JOUR
T1 - Recommendations for long-term luminance distribution measurements
T2 - the spatial resolution
AU - Kruisselbrink, Thijs W.
AU - Dangol, Rajendra
AU - van Loenen, Evert J.
PY - 2020/2
Y1 - 2020/2
N2 - Currently, luminance distribution measurement devices are increasingly used because there is high relevancy in the luminance distribution to the perceived visual comfort, also technology is maturing. It is now feasible to conduct long-term measurements and integrate these devices into lighting control systems. This, however, can result in new issues such as privacy controversies and high computational costs, induced by high spatial resolutions. Therefore, this study aims to propose a spatial resolution that is able to measure the luminance accurately while minimizing privacy sensitivity and computational costs. This is done based on luminance distribution measurements in office environments. The accuracy of lower resolution luminance distributions is tested for the mean and maximum luminance and the illuminance. Additionally, the ability to recognize faces is measured as an indicator for privacy-sensitive content. Finally, the processing time is measured as an indicator for the computational costs. The results show that for mean luminance or illuminance measurements the spatial resolution can be reduced significantly to 440 x 330 and 720 x 540 pixels, respectively. This spatial resolution does not compromise the accuracy while minimizing the ability of automated facial recognition and reducing the computational costs significantly. However, for maximum luminance measurements, a high resolution of 3000 x 2250 pixels is deemed appropriate, although this does allow automated facial recognition and results in high computation costs. A toolbox has been developed to assist others in choosing a relevant spatial resolution for their luminance camera during long term luminance measurements in typical office environments.
AB - Currently, luminance distribution measurement devices are increasingly used because there is high relevancy in the luminance distribution to the perceived visual comfort, also technology is maturing. It is now feasible to conduct long-term measurements and integrate these devices into lighting control systems. This, however, can result in new issues such as privacy controversies and high computational costs, induced by high spatial resolutions. Therefore, this study aims to propose a spatial resolution that is able to measure the luminance accurately while minimizing privacy sensitivity and computational costs. This is done based on luminance distribution measurements in office environments. The accuracy of lower resolution luminance distributions is tested for the mean and maximum luminance and the illuminance. Additionally, the ability to recognize faces is measured as an indicator for privacy-sensitive content. Finally, the processing time is measured as an indicator for the computational costs. The results show that for mean luminance or illuminance measurements the spatial resolution can be reduced significantly to 440 x 330 and 720 x 540 pixels, respectively. This spatial resolution does not compromise the accuracy while minimizing the ability of automated facial recognition and reducing the computational costs significantly. However, for maximum luminance measurements, a high resolution of 3000 x 2250 pixels is deemed appropriate, although this does allow automated facial recognition and results in high computation costs. A toolbox has been developed to assist others in choosing a relevant spatial resolution for their luminance camera during long term luminance measurements in typical office environments.
KW - Computational costs
KW - Face recognition
KW - Luminance camera
KW - Luminance distribution
KW - Privacy
KW - Resolution
UR - http://www.scopus.com/inward/record.url?scp=85075521881&partnerID=8YFLogxK
U2 - 10.1016/j.buildenv.2019.106538
DO - 10.1016/j.buildenv.2019.106538
M3 - Article
SN - 0360-1323
VL - 169
JO - Building and Environment
JF - Building and Environment
M1 - 106538
ER -