Detailed Three-Dimensional Building Façade Reconstruction: A Review on Applications, Data and Technologies

Klimkowska, Anna; Cavazzi, Stefano; Leach, Richard; Grebby, Stephen

Abstract

Urban environments are regions of complex and diverse architecture. Their reconstruction and representation as three-dimensional city models have attracted the attention of many researchers and industry specialists, as they increasingly recognise the potential for new applications requiring detailed building models. Nevertheless, despite being investigated for a few decades, the comprehensive reconstruction of buildings remains a challenging task. While there is a considerable body of literature on this topic, including several systematic reviews summarising ways of acquiring and reconstructing coarse building structures, there is a paucity of in-depth research on the detection and reconstruction of façade openings (i.e., windows and doors). In this review, we provide an overview of emerging applications, data acquisition and processing techniques for building façade reconstruc-tion, emphasising building opening detection. The use of traditional technologies from terrestrial and aerial platforms, along with emerging approaches, such as mobile phones and volunteered geography information, is discussed. The current status of approaches for opening detection is then examined in detail, separated into methods for three-dimensional and two-dimensional data. Based on the review, it is clear that a key limitation associated with façade reconstruction is process automation and the need for user intervention. Another limitation is the incompleteness of the data due to occlusion, which can be reduced by data fusion. In addition, the lack of available diverse benchmark datasets and further investigation into deep-learning methods for façade openings extraction present crucial opportunities for future research.

Citation

Klimkowska, A., Cavazzi, S., Leach, R., & Grebby, S. (2022). Detailed Three-Dimensional Building Façade Reconstruction: A Review on Applications, Data and Technologies. Remote Sensing, 14(11), 2579. https://doi.org/10.3390/rs14112579

• Journal Article Type: Review
• Acceptance Date: May 15, 2022
• Online Publication Date: May 27, 2022
• Publication Date: Jun 1, 2022
• Deposit Date: May 30, 2022
• Publicly Available Date: May 30, 2022
• Journal: Remote Sensing
• Electronic ISSN: 2072-4292
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 11
• Article Number: 2579
• Pages: 2579
• DOI: https://doi.org/10.3390/rs14112579
• Keywords: General Earth and Planetary Sciences
• Public URL: https://nottingham-repository.worktribe.com/output/8305394
• Publisher URL: https://www.mdpi.com/2072-4292/14/11/2579