Abstract
ABSTRACT Computer-aided 3D modelling is the standard design method in the architecture, engineering, construction, owner, operator (AECOO) industry and in lighting design. Applying a photogrammetric process, a sequence of images is used to reconstruct the geometry of a space or an object in a 3D model. Likewise, a calibrated digital camera is utilized to measure the surface luminance values of an environment or an object. We propose a workflow in which the geometry and the luminance values are measured simultaneously by combining these two measurement methods. The pipeline has been assessed and validated through the application to a case study, the Aalto Hall (Aalto University, Espoo, Finland), in order to understand its potential.
Highlights
In the architecture, engineering, construction, owner, operator (AECOO) industry, three-dimensional (3D) computer-aided modelling is applied to design in order to oversee construction and to maintain a building or built environment
We presented simultaneous imaging luminance photometry and photogrammetry applied to an indoor space through a case study and the 3D luminance point cloud created from the measurement
We presented a workflow where photogrammetric 3D reconstruction and imaging luminance photometry are performed from the same image set captured with a luminance-calibrated camera
Summary
In the architecture, engineering, construction, owner, operator (AECOO) industry, three-dimensional (3D) computer-aided modelling is applied to design in order to oversee construction and to maintain a building or built environment. Computer-aided 3D modelling is the standard method in lighting design (Roy, 2000; Shikder, Price, & Mourshed, 2009). Our aim is to develop and present (through a case study) a process allowing both the 3D reconstruction of interior geometry and luminance mapping from the same image set. By applying photogrammetry we reconstruct a 3D luminance point cloud and present the measuring of a 3D luminance map in indoor environments. The Results section shows the outcomes of our method: the luminance image locations and orientations, the 3D surface model and the 3D
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