通过预测人们的注意力来估计道路景观的美学服务:计算机视觉方法
Jun Qi1, Wenhui Li2, Zhaocheng Bai3
1College of Landscape Architecture and Horticulture, Southwest Forestry University, 650224, Kunming, Yunnan, China; Engineering Technology Research Center of National Forestry and Grassland Administration on Southwest Landscape Architecture, 650224, Kunming, Yunnan, China.
Journal of environmental management
|February 19, 2025
概括
计算机视觉通过识别视觉注意力模式来分析道路景观美学. 这种方法有助于规划风景公路,通过区分有吸引力的自然元素和没有吸引力的人工元素.
科学领域:
- 环境心理学 环境心理学
- 计算机视觉 计算机视觉
- 景观建筑 景观建筑 建筑
背景情况:
- 道路美学服务提供娱乐价值,并为景观道路规划提供信息.
- 分析审美注意力的传统方法有局限性.
- 计算机视觉为详细的景观分析提供像素级工具.
研究的目的:
- 开发和验证计算机视觉模型,用于预测道路景观中的美学注意力.
- 阐明正面和负面美学注意力的视觉特征和模式.
- 为规划和设计风景公路提供经验性见解.
主要方法:
- 收集了来自中国西南部的道路景观图像,并通过公众评分生成了美学标签.
- 采用两步深度转移学习方法来训练美学预测模型.
- 利用类激活映射,图像细分,色彩提取,深度估计和边缘检测来分析审美注意力.
主要成果:
- 审美预测模型在识别显著的美学特征时达到0.88的准确性.
- 负面的美学注意力集中在附近,淡淡的颜色,简单轮的人工物体上.
- 积极的美学注意力倾向于远处,鲜的颜色,复杂形状的自然物体,包括路边和道路末端的景观.
结论:
- 拟议的计算机视觉方法有效地估计了道路景观的美学服务.
- 确定了积极和消极审美关注的明显模式.
- 这些发现为优化风景道路指定,规划和设计提供了宝贵的意义.
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