Sequential Gaussian mixture models for two-level conditional random fields

Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review

Autorschaft

  • Sergey Kosov
  • Franz Rottensteiner
  • Christian Heipke

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Details

OriginalspracheEnglisch
Seiten (von - bis)153-163
Seitenumfang11
FachzeitschriftLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Jahrgang8142 LNCS
PublikationsstatusVeröffentlicht - 2013
Veranstaltung35th German Conference on Pattern Recognition, GCPR 2013 - Saarbrücken, Deutschland
Dauer: 3 Sept. 2013 → 6 Sept. 2013

Abstract

Conditional Random Fields are among the most popular techniques for image labelling because of their flexibility in modelling dependencies between the labels and the image features. This paper addresses the problem of efficient classification of partially occluded objects. For this purpose we propose a novel Gaussian Mixture Model based on a sequential training procedure, in combination with multi-level CRF-framework. Our approach is evaluated on urban aerial images. It is shown to increase the classification accuracy in occluded areas by up to 14,4%.

ASJC Scopus Sachgebiete

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Sequential Gaussian mixture models for two-level conditional random fields. / Kosov, Sergey; Rottensteiner, Franz; Heipke, Christian.
in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jahrgang 8142 LNCS, 2013, S. 153-163.

Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review

Kosov, S, Rottensteiner, F & Heipke, C 2013, 'Sequential Gaussian mixture models for two-level conditional random fields', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jg. 8142 LNCS, S. 153-163. https://doi.org/10.1007/978-3-642-40602-7_16
Kosov, S., Rottensteiner, F., & Heipke, C. (2013). Sequential Gaussian mixture models for two-level conditional random fields. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8142 LNCS, 153-163. https://doi.org/10.1007/978-3-642-40602-7_16
Kosov S, Rottensteiner F, Heipke C. Sequential Gaussian mixture models for two-level conditional random fields. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2013;8142 LNCS:153-163. doi: 10.1007/978-3-642-40602-7_16
Kosov, Sergey ; Rottensteiner, Franz ; Heipke, Christian. / Sequential Gaussian mixture models for two-level conditional random fields. in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2013 ; Jahrgang 8142 LNCS. S. 153-163.
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