Enhancing Point Cloud Segmentation of Chinese Historical Buildings with Synthetic Data
- DOI
- 10.2991/978-94-6463-650-5_15How to use a DOI?
- Keywords
- Historical buildings; Point cloud semantic segmentation; Synthetic dataset
- Abstract
Considering the challenges of segmenting architectural components in point cloud data, particularly for Chinese historical buildings, we develop an efficient method for constructing datasets to enhance deep learning techniques for precise segmentation. Surface sampling is integrated with advanced virtual laser scanning technology in our approach. Initially, labeled point cloud data is captured through surface sampling. Subsequently, the HELIOS++ simulation platform mimics real-world scanning to generate unlabeled data resembling actual point clouds. Precise alignment and label transfer between these two types of data result in an annotated dataset that preserves authentic scanning characteristics. Additionally, we introduce a symmetry-axis-based point cloud completion technique to address data loss during scanning, leveraging the inherent symmetry found in Chinese historical buildings. To validate the effectiveness of our dataset, two state-of-the-art deep learning models are selected for comprehensive evaluation. Experimental results demonstrate that our dataset supports efficient and stable model training, exhibits strong generalization capabilities, and provides a robust foundation for semantic segmentation of historical buildings.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jiangping Ma AU - Zhiyuan Guo AU - Wenpeng Li AU - Weiya Chen PY - 2025 DA - 2025/01/31 TI - Enhancing Point Cloud Segmentation of Chinese Historical Buildings with Synthetic Data BT - Proceedings of the 2024 7th International Conference on Civil Architecture, Hydropower and Engineering Management (CAHEM 2024) PB - Atlantis Press SP - 147 EP - 154 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-650-5_15 DO - 10.2991/978-94-6463-650-5_15 ID - Ma2025 ER -