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https://hdl.handle.net/2440/55407
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Type: | Conference paper |
Title: | Man-made structure segmentation using gaussian procesess and wavelet features. |
Author: | Zhou, H. Suter, D. |
Citation: | Proceedings of the 14th IEEE International Conference on Image Processing, San Antonio, Texas, USA., 2007: pp.IV-349-IV-352 |
Publisher: | IEEE |
Publisher Place: | Online |
Issue Date: | 2007 |
ISBN: | 1424414377 9781424414376 |
ISSN: | 1522-4880 |
Conference Name: | IEEE International Conference on Image Processing (14th : 2007 : San Antonio, Texas) |
Statement of Responsibility: | Hang Zhou and David Suter |
Abstract: | We apply Gaussian process classification (GPC) to man-made structure segmentation, treated as a two class problem. GPC is a discriminative approach, and thus focuses on modelling the posterior directly. It relaxes the strong assumption of conditional independence of the observed data (generally used in a generative model). In addition, wavelet transform features, which are effective in describing directional textures, are incorporated in the feature vector. Satisfactory results have been obtained which show the effectiveness of our approach. |
Keywords: | Man-made structure segmentation Gaussianprocess (GP) Gaussian process classification (GPC) Expectation Propagation (EP) wavelet transform. |
DOI: | 10.1109/ICIP.2007.4380026 |
Description (link): | http://dx.doi.org/10.1109/ICIP.2007.4380026 |
Published version: | http://dx.doi.org/10.1109/icip.2007.4380026 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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