APS
30th APS Annual Convention · 2018
Low-Level and Semantic Visual Features Predict Preference in Virtual Environments
- Muxuan Lyu
The University of Chicago - Kathryn Schertz
The University of Chicago - Kyoung whan Choe
The University of Chicago - Brent Chamberlain
Kansas State University - Xiaochun Qin
Beijing Jiaotong University - Michael Meitner
The University of British Columbia - Marc Berman
The University of Chicago
Abstract
We studied participants’ continuous preference ratings of six different video simulations of highway driving environments created using GIS-modeling. We found preference was predicted by semantic and low-level visual features. Additionally, continuous ratings gave a more nuanced understanding of preference over ratings of still images from the same environments.
Environment
