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步行者可访问的基础设施库存:为所有步行类型的多模式地理空间数据实现和评估零射击细分
Jiahao Xia1, Gavin Gong2, Jiawei Liu3
1Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Journal of imaging
|March 27, 2024
概括
本研究介绍了Segment Anything Model (SAM) 工作流程,用于从LiDAR和卫星数据中对行人基础设施进行细分. 该方法有效地创建可访问的基础设施库存,使城市规划人员和残疾人受益.
科学领域:
- 地理空间科学 地理空间科学
- 计算机视觉 计算机视觉
- 城市规划 城市规划
背景情况:
- 传统的行人基础设施库存往往省略了可访问性关键的街头家具.
- 移动LiDAR和卫星图像为基础设施绘图提供了丰富的数据.
- 细分任何模型 (SAM) 显示了对零射击细分任务的承诺.
研究的目的:
- 开发和优化基于SAM的工作流程,以从多来源的地理空间数据中对行人基础设施进行细分.
- 调查移动LiDAR和街景图像的使用,以创建全面的库存.
- 评估SAM在分割各种行人基础设施资产方面的表现.
主要方法:
- 设计并优化了对地理空间数据的分段任何模型 (SAM) 工作流.
- 使用移动LiDAR点云数据生成街景图像.
- 集成的街景图像与卫星图像进行多式联通输入.
- 采用零射击细分来识别行人基础设施和街头家具.
主要成果:
- 这种基于SAM的方法有效地从联合LiDAR衍生的街景和卫星图像中对行人基础设施进行细分.
- 来自移动LiDAR的街景图像,当与卫星数据配对时,便于有效的零拍摄细分.
- 该方法成功地扩大了行人基础设施的定义,包括可访问性特征.
结论:
- 拟议的工作流提供了一个可扩展和有效的方法,用于创建全面的行人可访问的基础设施库存.
- 这种方法为GIS专业人员,城市管理人员和交通规划人员提供了直接的好处.
- 这些发现特别支持对限制出行残疾人的改善可访问性.
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