{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T10:46:26Z","timestamp":1770979586052,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T00:00:00Z","timestamp":1759363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Symmetry"],"abstract":"<jats:p>Heritage Building Information Modelling (HBIM) requires the accurate classification of diverse building elements from 3D point clouds. This study presents a novel classification approach integrating a bespoke Uniclass-derived taxonomy with a hierarchical Random Forest model. It was applied to the 17th-century Queen\u2019s House in Greenwich, a building rich in classical architectural elements whose geometric properties are often defined by principles of symmetry. The bespoke classification was implemented across three levels (50 mm, 20 mm, 5 mm point cloud resolutions) and evaluated against the prior experiment that used Uniclass classification. Results showed a substantial improvement in classification precision and overall accuracy at all levels. The Level 1 classifier\u2019s accuracy increased by 15% of points (relative ~50% improvement) with the bespoke classification taxonomy, reducing the misclassifications and error propagation in subsequent levels. This research demonstrates that tailoring the Uniclass building classification for heritage-specific geometry significantly enhances machine learning performance, which, to date, has not been published in the academic domain. The findings underscore the importance of adaptive taxonomies and suggest pathways for integrating multi-scale features and advanced learning methods to support automated HBIM workflows.<\/jats:p>","DOI":"10.3390\/sym17101635","type":"journal-article","created":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T09:38:08Z","timestamp":1759397888000},"page":"1635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["From Symmetry to Semantics: Improving Heritage Point Cloud Classification with a Geometry-Aware, Uniclass-Informed Taxonomy for Random Forest Implementation in Automated HBIM Modelling"],"prefix":"10.3390","volume":"17","author":[{"given":"Aleksander","family":"Gil","sequence":"first","affiliation":[{"name":"Department of Architecture and Built Environment, Sutherland Building, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5705-2272","authenticated-orcid":false,"given":"Yusuf","family":"Arayici","sequence":"additional","affiliation":[{"name":"Department of Architecture and Built Environment, Sutherland Building, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,2]]},"reference":[{"key":"ref_1","unstructured":"RICS (2012). RICS New Rules of Measurment: NRM 1\u2013Order of Cost Estimating and Cost Planning for Capital Building Works, RICS."},{"key":"ref_2","unstructured":"NBS (2025, March 30). NBS Uniclass. Unified Construction Classification. Available online: https:\/\/www.thenbs.com\/our-tools\/uniclass-2015."},{"key":"ref_3","unstructured":"CSI (2025, March 30). OmniClass Construction Classification System (OCCS). OmniClass\u00ae. Available online: https:\/\/www.csiresources.org\/standards\/omniclass."},{"key":"ref_4","unstructured":"Svensk Byggtj\u00e4nst (2025, March 30). CoClass: A Classification System for the Built Environment. Available online: https:\/\/coclass.byggtjanst.se."},{"key":"ref_5","unstructured":"Molio (2025, March 30). CCS-Cuneco Classification System. Available online: https:\/\/molio.dk\/produkter\/digitale-vaerktojer\/gratis-vaerktojer\/ccs-cuneco-classification-system\/."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Salamanca, S., Merch\u00e1n, P., Espacio, A., P\u00e9rez, E., and Merch\u00e1n, M.J. (2024). Segmentation of 3D Point Clouds of Heritage Buildings Using Edge Detection and Supervoxel-Based Topology. Sensors, 24.","DOI":"10.20944\/preprints202405.2031.v1"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Altun, S., Cem G\u00fcne\u015f, M., H\u00fcseyin \u015eahin, Y., Mertan, A., \u00d6zkar, M., and \u00dcnal, G. (2022). Symmetry and Variance. Generative Parametric Modelling of Historical Brick Wall Patterns. Symmetry Art Sci., 96\u2013105.","DOI":"10.24840\/1447-607X\/2022\/12-11-096"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1158","DOI":"10.1109\/TMM.2023.3277281","article-title":"LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation","volume":"26","author":"Zhao","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Tian, Q., Zhang, P., Zhai, Y., Wang, Y., and Zou, Q. (2024). Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data. Genome Biol. Evol., 16.","DOI":"10.1093\/gbe\/evae102"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Croce, V., Caroti, G., De Luca, L., Jacquot, K., Piemonte, A., and V\u00e9ron, P. (2021). From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning. Remote Sens., 13.","DOI":"10.3390\/rs13030461"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.culher.2024.12.006","article-title":"Automated Heritage Building Component Recognition and Modelling Based on Local Features","volume":"71","author":"Pang","year":"2025","journal-title":"J. Cult. Herit."},{"key":"ref_12","unstructured":"Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, The MIT Press. Adaptive computation and machine learning."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"072037","DOI":"10.1088\/1757-899X\/768\/7\/072037","article-title":"An Improved Random Forest Model Applied to Point Cloud Classification","volume":"768","author":"Xue","year":"2020","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_14","first-page":"127","article-title":"Automated Mapping of Building Facades by Machine Learning","volume":"XL\u20133","year":"2014","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"25","DOI":"10.5194\/isprs-archives-XLII-2-W8-25-2017","article-title":"Segmentation of large unstructured point clouds usingoctree-based region growing and conditional random fields","volume":"XLII-2\/W8","author":"Bassier","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"399","DOI":"10.5194\/isprs-archives-XLII-2-399-2018","article-title":"From 2d to 3d supervised segmentation and classification for cultural heritage applications","volume":"XLII\u20132","author":"Grilli","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"541","DOI":"10.5194\/isprs-archives-XLII-2-W15-541-2019","article-title":"Geometric features analysis for the classification of cultural heritage point clouds","volume":"XLII-2\/W15","author":"Grilli","year":"2019","journal-title":"Int. Arch. Photogramm Remote Sens. Spat. Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Teruggi, S., Grilli, E., Russo, M., Fassi, F., and Remondino, F. (2020). A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification. Remote Sens., 12.","DOI":"10.3390\/rs12162598"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3970","DOI":"10.3390\/heritage5040204","article-title":"A Multilevel Multiresolution Machine Learning Classification Approach: A Generalization Test on Chinese Heritage Architecture","volume":"5","author":"Zhang","year":"2022","journal-title":"Heritage"},{"key":"ref_20","unstructured":"Li, Y., Bu, R., Sun, M., Wu, W., Di, X., and Chen, B. (2018, January 3\u20138). PointCNN: Convolution On X-Transformed Points. Proceedings of the Advances in Neural Information Processing Systems 31 (NeurIPS 2018), Montr\u00e9al, QC, Canada."},{"key":"ref_21","first-page":"1503","article-title":"3D Convolutional Neural Network for Semantic Scene Segmentation Based on Unstructured Point Clouds","volume":"14","author":"Zhang","year":"2018","journal-title":"IJPE"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Pupeikis, D., Navickas, A.A., Klumbyte, E., and Seduikyte, L. (2022). Comparative Study of Construction Information Classification Systems: CCI versus Uniclass 2015. Buildings, 12.","DOI":"10.3390\/buildings12050656"},{"key":"ref_23","unstructured":"buildingSMART (2025, March 30). Industry Foundation Classes (IFC): OpenBIM Data Schema for Building and Infrastructure. Available online: https:\/\/technical.buildingsmart.org\/standards\/ifc\/ifc-schema-specifications\/."},{"key":"ref_24","unstructured":"Haahtela-kehitys (2025, March 30). CCI Construction Classification International, Available online: https:\/\/koncepcebim.gov.cz\/bim\/co-je-co-v-bim\/cci\/."},{"key":"ref_25","unstructured":"NBS (2025, March 30). Historical Uniclass: The Restoration of the Houses of Parliament. Available online: https:\/\/www.thenbs.com\/knowledge\/historical-uniclass-the-restoration-of-the-houses-of-parliament."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"309","DOI":"10.5194\/isprs-archives-XLIII-B2-2020-309-2020","article-title":"Self-learning ontology for instance segmentation of 3d indoor point cloud","volume":"XLIII-B2-2020","author":"Poux","year":"2020","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Gil, A., and Arayici, Y. (2025). Point Cloud Segmentation Based on the Uniclass Classification System with Random Forest Algorithm for Cultural Heritage Buildings in the UK. Heritage, 8.","DOI":"10.3390\/heritage8050147"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"6","DOI":"10.21039\/rsj.326","article-title":"The Queen\u2019s House before Queen\u2019s House: Margaret of Anjou and Greenwich Palace, 1447\u20131453","volume":"8","author":"Delman","year":"2021","journal-title":"R. Stud. J."},{"key":"ref_29","unstructured":"Girardeau-Montaut, D. (2025, June 30). Cloud Compare. Available online: http:\/\/www.cloudcompare.org."},{"key":"ref_30","unstructured":"(2014). Information and Documentation\u2014A Reference Ontology for the Interchange of Cultural Heritage Information (Standard No. ISO 21127:2014)."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/10\/1635\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T09:48:30Z","timestamp":1759398510000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/10\/1635"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,2]]},"references-count":30,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["sym17101635"],"URL":"https:\/\/doi.org\/10.3390\/sym17101635","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,2]]}}}