使用边缘检测和基于超声波的拓学对遗产建筑的3D点云进行细分
Santiago Salamanca1, Pilar Merchán1, Alejandro Espacio1
1Departamento de Ingeniería Eléctrica, Electrónica y Automática, Escuela de Ingenierías Industriales, Universidad de Extremadura, Avda. Elvas s/n, 06006 Badajoz, Spain.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
这种新的无监督细分算法有效地细分了遗产建筑的杂3D点云. 它的性能优于现有的方法,可以准确识别建筑元素进行进一步分析.
科学领域:
- 计算机视觉 计算机视觉
- 数字遗产是数字遗产的一部分.
- 几何处理 几何处理
背景情况:
- 来自遗产建筑的3D点云往往表现出高变化和噪音.
- 准确的细分对于分析和保存数字遗产资产至关重要.
- 现有的细分方法可能会与杂和可变3D数据的复杂性作斗争.
研究的目的:
- 为3D点云引入一种新的,无监督的细分算法.
- 专门应对在遗产应用中常见的噪音数据和高可变性所带来的挑战.
- 为了促进对细分的3D建筑数据的后续分类和识别任务.
主要方法:
- 该算法采用边缘检测技术与基于图形的拓结构相结合.
- 3D点云的超声化生成了段定义的图形结构.
- 无监督方法不需要预先标记的数据,提高在遗产环境中的适用性.
主要成果:
- 该算法成功地将3D数据分割成不同的建筑元素.
- 与其他三种细分方法相比,在真实世界遗产建筑数据上表现出卓越的性能.
- 在历史结构中实现了平面和曲面表面的有效细分.
结论:
- 拟议的无监督细分算法是3D点云处理的宝贵工具,特别是在遗产应用中.
- 它能够适应不同的边缘检测和超声声化技术,从而实现灵活的实现.
- 该方法提供了准确的细分结果,支持进一步分析和对建筑元素的分类.
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