Open AccessNon-Intrusive Luminance Mapping via High Dynamic Range Imaging and 3-D Reconstruction
Author(s) -
Michael Kim,
Athanasios Tzempelikos
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2042/1/012113
Subject(s) - luminance , computer vision , computer science , artificial intelligence , high dynamic range , pipeline (software) , context (archaeology) , computer graphics (images) , photogrammetry , projection (relational algebra) , position (finance) , high dynamic range imaging , dynamic range , geography , economics , programming language , archaeology , finance , algorithm
Continuous luminance monitoring is challenging because high-dynamic-range cameras are expensive, they need programming, and are intrusive when placed near the occupants’ field-of-view. A new semi-automated and non-intrusive framework is presented for monitoring occupant-perceived luminance using a low-cost camera sensor and Structure-from- Motion (SfM)-Multiview Stereo (MVS) photogrammetry pipeline. Using a short video and a few photos from the occupant position, the 3D space geometry is automatically reconstructed. Retrieved 3D context enables the back-projection of the camera-captured luminance distribution into 3D spaces that are in turn re-projected to occupant-FOVs. The framework was tested and validated in a testbed office. The re-projected luminance field showed with good agreement with luminance measured at the occupant position. The new method can be used for non-intrusive luminance monitoring integrated with daylighting control applications.