CMU VASC seminar: Observations from Parsing Images of Architectural Scenes

Observations from Parsing Images of Architectural Scenes
Alexander Berg
UC Berkeley

Computational models for visual recognition show promise for some tasks. I will review our success in this area and show some information theoretic comparisons with our ongoing work on parsing scenes. For images of architectural scenes we have observed that very simple independent local features provide a great deal of information about what components -- building, sky, ground, etc. -- make up a scene. In addition a few carefully chosen image wide latent variables are added to the model then even more information is available. Finally given this coarse level parsing it is possible to effectively identify features such as windows and roof-lines that would be difficult to parse in isolation.