ACM CHI 2024

Experiential Views

Towards Human Experience Evaluation of Designed Spaces using Vision-Language Models

A screen capture of Experiential View’s floor plan visualization and WebGL-based 3D viewer integration user interface.

Abstract

Experiential Views is a proof-of-concept in which we explore a method of helping architects and designers predict how building occupants might experience their designed spaces using AI technology based on Vision-Language Models. Our prototype evaluates a space using a pre-trained model that we fine-tuned with photos and renders of a building. These images were evaluated and labeled based on a preliminary set of three human-centric dimensions that characterize the Social, Tranquil, and Inspirational qualities of a scene. We developed a floor plan visualization and a WebGL-based 3D-viewer that demonstrate how architectural design software could be enhanced to evaluate areas of a built environment based on psychological or emotional criteria. We see this as an early step towards helping designers anticipate emotional responses to their designs to create better experiences for occupants.

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