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Gabor wavelet networks for object representation

Krüger, Volker LU orcid and Sommer, Gerald (2001) 10th International Workshop on Theoretical Foundations of Computer Vision, 2000 In Lecture Notes in Computer Science 2032. p.115-128
Abstract

In this article we want to introduce first the Gabor wavelet network as a model based approach for an effective and efficient object representation. The Gabor wavelet network has several advantages such as invariance to some degree with respect to translation, rotation and dilation. Furthermore, the use of Gabor filters ensured that geometrical and textural object features are encoded. The feasibility of the Gabor filters as a model for local object features ensures a considerable data reduction while at the same time allowing any desired precision of the object representation ranging from a sparse to a photo-realistic representation. In the second part of the paper we will present an approach for the estimation of a head pose that is... (More)

In this article we want to introduce first the Gabor wavelet network as a model based approach for an effective and efficient object representation. The Gabor wavelet network has several advantages such as invariance to some degree with respect to translation, rotation and dilation. Furthermore, the use of Gabor filters ensured that geometrical and textural object features are encoded. The feasibility of the Gabor filters as a model for local object features ensures a considerable data reduction while at the same time allowing any desired precision of the object representation ranging from a sparse to a photo-realistic representation. In the second part of the paper we will present an approach for the estimation of a head pose that is based on the Gabor wavelet networks.

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Please use this url to cite or link to this publication:
author
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publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Multi-Image Analysis : 10th International Workshop on Theoretical Foundations of Computer Vision, Revised Papers - 10th International Workshop on Theoretical Foundations of Computer Vision, Revised Papers
series title
Lecture Notes in Computer Science
editor
Klette, Reinhard ; Gimel’farb, Georgy and Huang, Thomas
volume
2032
pages
14 pages
publisher
Springer
conference name
10th International Workshop on Theoretical Foundations of Computer Vision, 2000
conference location
Dagstuhl Castle, Germany
conference dates
2000-03-12 - 2000-03-17
external identifiers
  • scopus:84872563097
ISSN
0302-9743
1611-3349
ISBN
354042122X
9783540421221
DOI
10.1007/3-540-45134-X_9
language
English
LU publication?
no
id
b481f384-759e-4772-8c58-14b97f4f13ed
date added to LUP
2019-07-08 21:28:40
date last changed
2024-01-01 15:54:21
@inbook{b481f384-759e-4772-8c58-14b97f4f13ed,
  abstract     = {{<p>In this article we want to introduce first the Gabor wavelet network as a model based approach for an effective and efficient object representation. The Gabor wavelet network has several advantages such as invariance to some degree with respect to translation, rotation and dilation. Furthermore, the use of Gabor filters ensured that geometrical and textural object features are encoded. The feasibility of the Gabor filters as a model for local object features ensures a considerable data reduction while at the same time allowing any desired precision of the object representation ranging from a sparse to a photo-realistic representation. In the second part of the paper we will present an approach for the estimation of a head pose that is based on the Gabor wavelet networks.</p>}},
  author       = {{Krüger, Volker and Sommer, Gerald}},
  booktitle    = {{Multi-Image Analysis : 10th International Workshop on Theoretical Foundations of Computer Vision, Revised Papers}},
  editor       = {{Klette, Reinhard and Gimel’farb, Georgy and Huang, Thomas}},
  isbn         = {{354042122X}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  month        = {{05}},
  pages        = {{115--128}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{Gabor wavelet networks for object representation}},
  url          = {{http://dx.doi.org/10.1007/3-540-45134-X_9}},
  doi          = {{10.1007/3-540-45134-X_9}},
  volume       = {{2032}},
  year         = {{2001}},
}