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Hierarchical Segment Support for Categorical Image Labeling
AbstractThis paper introduces a novel method for categorical image labeling, where each pixel is uniquely assigned to one of a set of unordered, discrete labels. Starting from provided label-depending pixel likelihoods we (a) exploit a segment hierarchy as spatial support to define powerful priors and (b) introduce an efficient and effective inference method, that can be implemented in a few lines of code. Experiments show that competitive labeling accuracy compared to related discrete, continuous, segmentation and filtering approaches is achieved.
Related Material
[pdf][bibtex]@InProceedings{Donoser_2013_ICCV_Workshops,
author = {Michael Donoser and Hayko Riemenschneider},
title = {Hierarchical Segment Support for Categorical Image Labeling},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}
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