CRII: CHS: Perceptual Data-Guided Computational Design

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Perception determines how humans interpret and make use of designs, and is therefore an important consideration for design. This CRII project investigates how perceptual data can be used to guide computational design processes. As a showcase, the PI will investigate how visual perception data obtained from virtual environments can be used to devise novel computational approaches capable of analyzing, visualizing and modeling the human affordance aspects of given architectural layouts. Such approaches can be applied for generating functional layout designs for a variety of built environments, to enhance movement comfort, efficiency, productivity and safety. The proposed research will bring broad impacts on improving transportation, tourism, commerce and public safety. In addition, the PI will contribute by disseminating the collected visual perception datasets; organizing vision and cognition workshops regularly; mentoring a team of undergraduate, master and PhD students to conduct research, including minority students whom the PI will mentor via the McNair Scholars Program.In particular, the PI will set up a virtual reality platform equipped with eyetracking capabilities for studying human visual perception and reactions towards different geometric, spatial and semantic features in 3D environments. The collected data will form the basis for developing a 3D scene analysis tool which designers can use to visualize and understand the effects of layout designs on human visual perception and people flow, to make informed design choices. Designers can also easily obtain ergonomic design suggestions via suggestive interfaces driven by an optimization component which considers multiple visual perception and human affordance factors. Based on the visual perception data, an optimization approach will also be devised capable of automatically generating and enhancing 3D layout designs.