A suggestion method for urban perception improvement using street-view images

Jinhao Sun; Yi Zhang; Xi Yang

doi:10.1117/12.2683558

26 June 2023 A suggestion method for urban perception improvement using street-view images

Jinhao Sun, Yi Zhang, Xi Yang

Author Affiliations +

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 127211K (2023) https://doi.org/10.1117/12.2683558
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

The evaluation of street view perception plays a crucial role in the design and improvement of urban street layouts by urban planners. However, the most commonly used method for evaluating street views by planners and researchers is through questionnaires, which may not effectively capture users' psychological feelings. Currently, there is a lack of research on providing suggestions for improving street views that score low in perception evaluation. To address this issue, we propose a method for highlighting areas where street views are insufficient in six aspects which are beautiful, safety, wealthy, lively, boring and depressing to provide suggestions for improvement. Reference pictures and corresponding improvements suggested by the proposed system are necessary as they can provide urban planners with intuitive suggestions for street improvement. In this study, we recruit volunteers to rate street view maps in the six aspects mentioned above. We then use the scene graph generation method to characterize the relationship between objects in the street view images. Finally, we apply the graph-matching algorithm SimGNN to identify three pictures that are highly similar to the graph structure of the high-score street views as reference images. This approach effectively provides suggestions for street view images with low-score, while also offering an intuitive way to improve street view perception for urban planners. Overall, our proposed method provides a more comprehensive and effective way to evaluate and improve street views, which can contribute to better urban planning and design.

Citation Download Citation

Jinhao Sun, Yi Zhang, and Xi Yang "A suggestion method for urban perception improvement using street-view images", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 127211K (26 June 2023); https://doi.org/10.1117/12.2683558

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KEYWORDS

Object detection

Education and training

Safety

Feature extraction

Design and modelling

Image segmentation

Analytical research

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