CVNov 25, 2023

View-Based Luminance Mapping in Open Workplace

CMU
arXiv:2311.14927v11 citationsh-index: 8
Originality Synthesis-oriented
AI Analysis

This addresses daylight design optimization for building occupants, but it is incremental as it builds on existing luminance mapping techniques with a specific workflow.

The paper tackles the problem of improving daylight performance in open workplaces by mapping indoor luminance values to the facade, using a computational method that filters high luminance from 3D hemispheres derived from fisheye renderings to identify areas with excessive light penetration.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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