A room with a view: Automatic assessment of window views for high-rise high-density areas using City Information Models and deep transfer learning
Four Window View Indices (WVIs) were defined for measuring outside greenery, water-body, sky, and construction views.
WVIs complemented existing view indices from the ground, aircraft, and satellites for urban computing.
City Information Model (CIM)-based view images were trustworthy data sources for WVIs.
Automatic WVI assessment based on deep transfer learning with an ML regression layer was performed.
Highly satisfactory (R2 > 0.95) and fast (3.08 s/view) assessment results from experimental tests were obtained.