License: Creative Commons Attribution-NoDerivs 3.0 Unported license (CC BY-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.VLUDS.2011.89
URN: urn:nbn:de:0030-drops-37437
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2012/3743/
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Salz, Peter ; Reis, Gerd ; Stricker, Didier

Texture-based Tracking in mm-wave Images

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Abstract

Current tracking methods rely on color-, intensity-, and edge-based features to compute a description of an image region. These approaches are not well-suited for low-quality images such as mm-wave data from full-body scanners. In order to perform tracking in such challenging grayscale images, we propose several enhancements and extensions to the Visual Tracking Decomposition (VTD) by Kwon and Lee. A novel region descriptor, which uses texture-based features, is presented and integrated into VTD. We improve VTD by adding a sophisticated weighting scheme for observations, better motion models, and a more realistic way for sampling and interaction. Our method not only outperforms VTD on mm-wave data but also has comparable results on normal-quality images. We are confident that our region descriptor can easily be extended to other kinds of features and applications such that tracking can be performed in a large variety of image data, especially low-resolution, low-illumination and noisy images.

BibTeX - Entry

@InProceedings{salz_et_al:OASIcs:2012:3743,
  author =	{Peter Salz and Gerd Reis and Didier Stricker},
  title =	{{Texture-based Tracking in mm-wave Images}},
  booktitle =	{Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011},
  pages =	{89--101},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-46-0},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{27},
  editor =	{Christoph Garth and Ariane Middel and Hans Hagen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2012/3743},
  URN =		{urn:nbn:de:0030-drops-37437},
  doi =		{10.4230/OASIcs.VLUDS.2011.89},
  annote =	{Keywords: Visual Tracking decomposition, low-quality images, texture features, mm-wave imagery}
}

Keywords: Visual Tracking decomposition, low-quality images, texture features, mm-wave imagery
Collection: Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2011
Issue Date: 2012
Date of publication: 16.10.2012

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