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Lookup NU author(s): Dr Mela Bettega
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© 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Citizens’ engagement in urban design often involves workshops where design proposals are presented to residents through professional drawings. However, traditional analog methods can pose challenges for non-expert participants, particularly in terms of spatial visualization and effectively expressing their design ideas. Derived from the first authors’ experience working in a participatory design process and post-interviews with the participants, we highlight the need for intuitive human-perspective rendering, user-friendly interaction for requirements expression, and collective feedback visualization. In response, we developed ManyViews, a tool designed to enhance the participatory design process by enabling the envisioning of design proposals and integrating diverse viewpoints from the community. ManyViews incorporates a three-stage pipeline: view transformation generates consistent human-perspective renderings for locations in a masterplan with generative models; rendering edition enables user-friendly expression of design suggestions for the environment through cross-modal editing on human-perspective renderings; and viewpoint visualization traces and compiles the evolution of diverse designs from multiple participants with provenance visualization. User studies demonstrate that ManyViews reduces communication barriers between non-experts and professionals, enhancing citizen engagement as collaborators in public open space co-design.
Author(s): Huang R, Hou Y, Bettega M, Zhang K, Zeng W
Publication type: Article
Publication status: Published
Journal: International Journal of Human Computer Studies
Year: 2026
Volume: 211
Print publication date: 01/04/2026
Online publication date: 10/03/2026
Acceptance date: 06/03/2026
ISSN (print): 1071-5819
ISSN (electronic): 1095-9300
Publisher: Academic Press
URL: https://doi.org/10.1016/j.ijhcs.2026.103796
DOI: 10.1016/j.ijhcs.2026.103796
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