ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLII-2-W7-367-2017 THE ISPRS BENCHMARK ON INDOOR MODELLING Khoshelham K. 1 Díaz Vilariño L. 2 3 Peter M. 4 Kang Z. 5 Acharya D. 1 Dept. of Infrastructure Engineering, The University of Melbourne, Parkville 3010 Australia Applied Geotechnologies Group, Dept. of Natural Resources and Environmental Engineering, University of Vigo, Spain GIS Technology, OTB Research Institute for the Built Environment, Delft University of Technology, Julianalaan 134, Delft, the Netherlands Dept. of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, the Netherlands Dept. of Remote Sensing and Geo-Information Engineering, School of Land Science and Technology, China University of Geosciences, Beijing 100083, China 12 09 2017 XLII-2/W7 367 372 Copyright: © 2017 K. Khoshelham et al. 2017 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLII-2-W7/367/2017/isprs-archives-XLII-2-W7-367-2017.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-2-W7/367/2017/isprs-archives-XLII-2-W7-367-2017.pdf

Automated generation of 3D indoor models from point cloud data has been a topic of intensive research in recent years. While results on various datasets have been reported in literature, a comparison of the performance of different methods has not been possible due to the lack of benchmark datasets and a common evaluation framework. The ISPRS benchmark on indoor modelling aims to address this issue by providing a public benchmark dataset and an evaluation framework for performance comparison of indoor modelling methods. In this paper, we present the benchmark dataset comprising several point clouds of indoor environments captured by different sensors. We also discuss the evaluation and comparison of indoor modelling methods based on manually created reference models and appropriate quality evaluation criteria. The benchmark dataset is available for download at: <a href="http://www2.isprs.org/commissions/comm4/wg5/benchmark-on-indoor-modelling.html"target="_blank">http://www2.isprs.org/commissions/comm4/wg5/benchmark-on-indoor-modelling.html</a>.