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Jampani, V., Gadde, R. and Gehler, P.V. (2015) Efficient Facade Segmentation Using Auto-Context. Proceedings of the IEEE Winter Conference on Applications of Computer Vision, Hawaii, 5-9 January 2015, 1038-1045. https://doi.org/10.1109/wacv.2015.143

has been cited by the following article:

• TITLE: Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

  AUTHORS: Zijian Zhang, Jicang Wu

  KEYWORDS: 3D Laser Scanning Point Clouds, Building Facade Segmentation, Point Cloud Processing, Feature Descriptors

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.6, June 28, 2024

  ABSTRACT: To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.