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arXiv · 1901.10772

Human-centric light sensing and estimation from RGBD images: The invisible light switch

Theodore Tsesmelis·Irtiza Hasan·Marco Cristani·Alessio Del Bue·Fabio Galasso
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Abstract

Lighting design in indoor environments is of primary importance for at least two reasons: 1) people should perceive an adequate light; 2) an effective lighting design means consistent energy saving. We present the Invisible Light Switch (ILS) to address both aspects. ILS dynamically adjusts the room illumination level to save energy while maintaining constant the light level perception of the users. So the energy saving is invisible to them. Our proposed ILS leverages a radiosity model to estimate the light level which is perceived by a person within an indoor environment, taking into account the person position and her/his viewing frustum (head pose). ILS may therefore dim those luminaires, which are not seen by the user, resulting in an effective energy saving, especially in large open offices (where light may otherwise be ON everywhere for a single person). To quantify the system performance, we have collected a new dataset where people wear luxmeter devices while working in office rooms. The luxmeters measure the amount of light (in Lux) reaching the people gaze, which we consider a proxy to their illumination level perception. Our initial results are promising: in a room with 8 LED luminaires, the energy consumption in a day may be reduced from 18585 to 6206 watts with ILS (currently needing 1560 watts for operations). While doing so, the drop in perceived lighting decreases by just 200 lux, a value considered negligible when the original illumination level is above 1200 lux, as is normally the case in offices.

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Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Alessio Del Bue, Fabio Galasso. 2019-01-30. Human-centric light sensing and estimation from RGBD images: The invisible light switch. https://arxiv.org/abs/1901.10772

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