城市绿蓝空间的实时基于传感器和自我报告的情感感知:利用FER和SAM探索性别差异
Xuan Zhang1, Haoying Han1,2,3, Guoqiang Shen1
1College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
这项研究揭示了针对城市绿蓝空间 (UGBS) 的性别特异性情绪反应. 面部表情识别技术为男性和女性如何不同地体验这些环境提供了新的见解,有助于包容性城市规划.
科学领域:
- 环境心理学 环境心理学
- 城市规划 城市规划
- 人与计算机的交互
背景情况:
- 城市绿蓝空间 (UGBS) 对幸福至关重要.
- 有限的研究存在于实时,性别特异性的UGBS的情绪反应.
- 了解这些差异对于公平的城市设计至关重要.
研究的目的:
- 在UGBS的实时情感评估中调查性别差异.
- 用双方法方法探索主观和客观的情绪反应.
- 在这种情况下,评估面部表情识别 (FER) 技术的实用性.
主要方法:
- 这是一种双方法方法,结合了自我报告的测量和面部表情识别 (FER).
- 静态图像 (谷歌街景) 和360度视频被用作刺激.
- 实验涉及108名参与者,产生超过200万个数据点与FER.
主要成果:
- 确定了不同的性别特异性情绪模式.
- 女性报告了更强烈的愉快情绪,并更喜欢更高的兴奋场景.
- 男人表现出更清晰的反应,更喜欢高峰值场景;草在女性中唤起放松,在男性中唤起兴奋,而蓝色空间在两者中都引起了平静.
结论:
- 面部表情识别 (FER) 技术显示了评估城市环境的实时情绪反应的潜力.
- 调查结果为包容性城市规划提供了可操作的见解,以增强情感福祉.
- 集成先进的工具可以帮助创造更宜居的城市,满足各种用户需求.
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