Title :
Bayesian model identification: Application to building reconstruction in aerial imagery
Author :
Cord, Matthieu ; Declercq, David
Author_Institution :
ESAT, Katholieke Univ., Leuven, Heverlee, Belgium
Abstract :
In this paper, we deal with building reconstruction in stereoscopic aerial imagery. We present a statistical, and competitive approach to the segmentation of roofs in pre-segmented regions. This parametric method is based on a multi-plane model, interpreted as a Bayesian mixture model. The so-called augmentation of the model with indicator variables allows the using of Bayesian sampler algorithms to achieve both the estimation of the model´s parameters and the segmentation of the selected region
Keywords :
Bayes methods; image reconstruction; image segmentation; stereo image processing; Bayesian mixture model; Bayesian model identification; Bayesian sampler algorithms; building reconstruction; indicator variables; multi-plane model; roof segmentation; segmentation; stereoscopic aerial imagery; Bayesian methods; Buildings; Ear; Image reconstruction; Image resolution; Image segmentation; Noise level; Radiometry; Shape; Writing;
Conference_Titel :
Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-5467-2
DOI :
10.1109/ICIP.1999.817087