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- Title
HIGH QUALITY FACADE SEGMENTATION BASED ON STRUCTURED RANDOM FOREST, REGION PROPOSAL NETWORK AND RECTANGULAR FITTING.
- Authors
Rahmani, Kujtim; Mayer, Helmut
- Abstract
In this paper we present a pipeline for high quality semantic segmentation of building facades using Structured Random Forest (SRF), Region Proposal Network (RPN) based on a Convolutional Neural Network (CNN) as well as rectangular fitting optimization. Our main contribution is that we employ features created by the RPN as channels in the SRF.We empirically show that this is very effective especially for doors and windows. Our pipeline is evaluated on two datasets where we outperform current state-of-the-art methods. Additionally, we quantify the contribution of the RPN and the rectangular fitting optimization on the accuracy of the result.
- Subjects
FACADE design &; construction; IMAGE segmentation; IMAGE analysis
- Publication
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 2018, Vol 4, Issue 2, p223
- ISSN
2194-9042
- Publication type
Article
- DOI
10.5194/isprs-annals-IV-2-223-2018