@inproceedings{e0e78a9f0d6946f78d813a0e76b6d65f,
title = "Linear Regression Based Self-intersection Detection Algorithm of B{\'e}zier Surfaces",
abstract = "Surface self-intersection detection plays an important role in industrial software such as geometric modeling, CAD and CAE, which is essential for ensuring the geometric consistency and construction stability of the model. This paper presents a linear regression-based self-intersection detection method of B{\'e}zier surfaces. By constructing a sample set of B{\'e}zier surfaces, the input features and regression labels are settled based on spatial point pairs which associated with geometric and parametric distance. A linear regression algorithm of surface self-intersection is proposed to learn the mapping relationship between the point pairs. To address the imbalance in the distribution of self-intersecting and non-self-intersecting samples, the ADASYN adaptive sampling method is given for sample enhancement. The experimental results show that the new algorithm significantly reduces the misjudgment rate while maintaining high detection accuracy of surface self-intersection.",
keywords = "B{\'e}zier surface, CAD, linear regression, self-intersection detection",
author = "Kexin Cao and Aizeng Wang and Zhenhao Wu and Tao Ning",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.; 10th International Symposium on Artificial Intelligence and Robotics, ISAIR 2025 ; Conference date: 24-08-2025 Through 26-08-2025",
year = "2026",
doi = "10.1007/978-981-95-4821-7\_19",
language = "英语",
isbn = "9789819548200",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "221--231",
editor = "Huimin Lu",
booktitle = "Artificial Intelligence and Robotics - 10th International Symposium, ISAIR 2025, Revised Selected Papers",
address = "德国",
}