The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W8
https://doi.org/10.5194/isprs-archives-XLII-2-W8-45-2017
https://doi.org/10.5194/isprs-archives-XLII-2-W8-45-2017
13 Nov 2017
 | 13 Nov 2017

SCAN-TO-BIM OUTPUT VALIDATION: TOWARDS A STANDARDIZED GEOMETRIC QUALITY ASSESSMENT OF BUILDING INFORMATION MODELS BASED ON POINT CLOUDS

M. Bonduel, M. Bassier, M. Vergauwen, P. Pauwels, and R. Klein

Keywords: geometric quality assessment, scan-to-BIM, standardization, Building Information Modeling, point clouds

Abstract. The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.