A Three-Layered Approach to Facade Parsing

author: Anđelo Martinović, KU Leuven
chairman: Tinne Tuytelaars, Faculty of Engineering, KU Leuven
chairman: Serge J. Belongie, University of California, San Diego
published: Nov. 12, 2012,   recorded: October 2012,   views: 211
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

We propose a novel three-layered approach for semantic segmentation of building facades. In the first layer, starting from an oversegmentation of a facade, we employ the recently introduced machine learning technique Recursive Neural Networks (RNN) to obtain a probabilistic interpretation of each segment. In the second layer, initial labeling is augmented with the information coming from specialized facade component detectors. The information is merged using a Markov Random Field. In the third layer, we introduce weak architectural knowledge, which enforces the final reconstruction to be architecturally plausible and consistent. Rigorous tests performed on two existing datasets of building facades demonstrate that we significantly outperform the current-state of the art, even when using outputs from earlier layers of the pipeline. Also, we show how the final output of the third layer can be used to create a procedural reconstruction.

See Also:

Download slides icon Download slides: eccv2012_martinovic_parsing_01.pdf (18.6 MB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: