  This paper introduces a novel computational method for mapping indoor
luminance values on the facade of an open workplace to improve its daylight
performance. 180-degree fisheye renderings from different indoor locations,
view positions, and times of the year are created. These renderings are then
transformed from two-dimensional (2D) images into three-dimensional (3D)
hemispheres. High luminance values are filtered and projected from the
hemisphere to the facade surface. This framework will highlight the areas of
the facade that allow too much light penetration into the interior environment.
The flexible workflow allows occupant centric lighting analysis that computes
multiple design parameters and synthesizes results for localized facade
optimization and daylight design.
