  Illumination is important for well-being, productivity and safety across
several environments, including offices, retail shops and industrial
warehouses. Current techniques for setting up lighting require extensive and
expert support and need to be repeated if the scene changes. Here we propose
the first fully-automated light management system (LMS) which measures lighting
in real-time, leveraging an RGBD sensor and a radiosity-based light propagation
model. Thanks to the integration of light distribution and perception curves
into the radiosity, we outperform a commercial software (Relux) on a newly
introduced dataset. Furthermore, our proposed LMS is the first to estimate both
the presence and the attention of the people in the environment, as well as
their light perception. Our new LMS adapts therefore lighting to the scene and
human activity and it is capable of saving up to 66%, as we experimentally
quantify,without compromising the lighting quality.
