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Hybrid object detection using improved Gaussian mixture model
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-0079-9049
2011 (English)In: 11 International Conference on Control, Automation and Systems (ICCAS2011): 26-29 October 2011, Kintex, Korea, Piscataway, NJ: IEEE Communications Society, 2011, p. 1475-1479Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a novel approach to detect moving objects in a complex background. The Gaussian mixture model (GMM) is an effective way to extract moving objects from a video sequence. However, the conventional mixture Gaussian method suffers from false motion detection in complex backgrounds and slow convergence. This work, in order to achieve robust and accurate extraction of the shapes of moving objects, applies a hybrid method to remove noise from images. The proposed model consists of two stages. The first stage consists of a fourth order PDE and the second stage is a relaxed median Experimental results show that the proposed model performs well even in the presence of higher levels of noise.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2011. p. 1475-1479
Series
International Conference on Control, Automation and Systems, ISSN 2093-7121
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-29623Local ID: 3296bb97-ca98-4e0d-972d-93fea3ed9505ISBN: 978-89-93215-03-8 (print)OAI: oai:DiVA.org:ltu-29623DiVA, id: diva2:1002847
Conference
International Conference on Control, Automation and Systems : 26/10/2011 - 29/10/2011
Note
Validerad; 2011; 20110702 (ahmfak)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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