Urban Perception Assessment from Street View Images Based on a Multifeature Integration Encompassing Human Visual Attention
Bibliographic Data
| ID | 3186843 |
|---|---|
| Authors | Nai Yang (0000-0001-5306-1163, China University of Geosciences (Beijing)), Zhitao Deng (0009-0005-6408-6602, China University of Geosciences (Beijing)), Fangtai Hu (China University of Geosciences (Beijing)), Qingfeng Guan (0000-0002-7392-3709, China University of Geosciences, corresponding author), Yi Chao (0000-0002-7286-5439), Chao Yi (0000-0002-1822-7890, China University of Geosciences (Beijing)), Lin Wan (0000-0002-9320-3725, China University of Geosciences (Beijing)) |
| Year | 2024 |
| Volume | 114 |
| Issue | 7 |
| Pages | 1424-1442 |
| Publication date | 2024-08-08 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2024.2363783 |
| OpenAlex | W4400406469 |
| Language | EN |
| Citations received | 8 |
| References cited | 46 |
Urban perception is a multifaceted process, spanning from vision to cognitive interpretation. Earlier studies on urban perception assessment have primarily concentrated on the analysis of graphic features of street view images such as color or semantic elements, neglecting the vital human sensory fixation features in cognitive processes. This study leveraged eye-tracking technology to accumulate human visual attention data during emotion scoring of street view images. Additionally, a deep learning network model was proposed to forecast human visual attention areas by assimilating environmental features such as image color, depth, and semantic elements, and subsequently amalgamating the aforementioned environmental features and visual attention to establish a perception prediction model, capable of predicting urban perception on a larger scale. Finally, the reliability and superiority of the urban perception prediction method were confirmed through ablation experiments and bias analysis. On the one hand, the method enhances the prediction accuracy of urban perception; on the other, it investigates the comprehensive influence of multiple features on human subjective emotions from the external environment perspective and individual perspective. This approach transcends the former limited reliance on single-image features, providing a novel and scientific approach for assessing urban perception
Cognitive psychology · Computer vision · Perception · Political science · Sociology · Automated Road and Building Extraction · Computer Science · Law · Psychology · Urban Studies · Video Surveillance and Tracking Methods · Visual Attention and Saliency Detection
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| Unique citing works | 8 |
|---|---|
| Citations per year | 8 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 8 |