室内地理,用于分析全球生活方式,使用计算机视觉
Martina Mazzarello1, Mikita Klimenka2, Rohit Sanatani2
1Senseable City Lab Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA. mmazz@mit.edu.
Scientific reports
|October 15, 2025
概括
尽管全球化,但在室内生活空间仍然存在当地文化差异. 对80个城市的40万多张Airbnb图像进行视觉AI分析,揭示了地理接近,全球化和室内设计之间的重要相关性,证实了持久的本地身份.
科学领域:
- 城市研究 城市研究
- 文化地理学 文化地理学
- 人工智能的人工智能
背景情况:
- 理论上说,全球化是为了减少当地的文化差异.
- 室内生活空间是关键的文化指标,但在这个背景下被研究不足.
- 了解全球力量如何影响当地美学至关重要.
研究的目的:
- 研究全球化对室内生活空间视觉特征的影响.
- 量化地理接近,全球化和室内设计多样性之间的关系.
- 评估面对全球化趋势的当地文化认同的持久性.
主要方法:
- 使用深度学习分类模型开发视觉AI框架.
- 利用一个庞大的数据集,包括来自80个城市的40万多张Airbnb图像.
- 梯度加权类激活映射 (Grad-CAM) 和统计分析的应用.
主要成果:
- 在室内空间的地理接近和视觉特征之间发现了显著的相关性 (R = 0.23-0.30).
- 全球化的程度也与室内空间的视觉特征有显著的相关性 (R ≈ 0.47).
- 尽管存在全球趋势,但在室内设计中仍有明显的当地特色.
结论:
- 尽管全球化的压力,室内生活空间的当地文化区别仍然具有弹性.
- 视觉AI为分析建筑环境中的文化多样性提供了一种新的方法.
- 该研究强调了全球力量与当地文化表达之间的复杂相互作用.
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