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Appearance-based 3-D face recognition from video

Krüger, Volker LU orcid ; Gross, Ralph and Baker, Simon (2002) 24th Symposium of the German Pattern Recognition Association, DAGM 2002 In Lecture Notes in Computer Science 2449. p.566-574
Abstract

In this work we present an appearance-based 3-D Face Recognition approach that is able to recognize faces in video sequences, independent from face pose. For this we combine eigen light-fields with probabilistic propagation over time for evidence integration. Eigen light-fields allow us to build an appearance based 3-D model of an object; probabilistic methods for evidence integration are attractive in this context as they allow a systematic handling of uncertainty and an elegant way for fusing temporal information. Experiments demonstrate the effectiveness of our approach. We tested this approach successfully on more than 20 testing sequences, with 74 different individuals.

Please use this url to cite or link to this publication:
author
; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Pattern Recognition : 24th DAGM Symposium Zurich, Switzerland, September 16–18, 2002 Proceedings - 24th DAGM Symposium Zurich, Switzerland, September 16–18, 2002 Proceedings
series title
Lecture Notes in Computer Science
volume
2449
pages
9 pages
publisher
Springer
conference name
24th Symposium of the German Pattern Recognition Association, DAGM 2002
conference location
Zurich, Switzerland
conference dates
2002-09-16 - 2002-09-18
external identifiers
  • scopus:84878550479
ISSN
0302-9743
1611-3349
ISBN
354044209X
9783540442097
DOI
10.1007/3-540-45783-6_68
language
English
LU publication?
no
id
4190f9a2-b18d-4b5d-8689-33984124e04f
date added to LUP
2019-07-08 21:25:26
date last changed
2024-01-01 15:54:20
@inproceedings{4190f9a2-b18d-4b5d-8689-33984124e04f,
  abstract     = {{<p>In this work we present an appearance-based 3-D Face Recognition approach that is able to recognize faces in video sequences, independent from face pose. For this we combine eigen light-fields with probabilistic propagation over time for evidence integration. Eigen light-fields allow us to build an appearance based 3-D model of an object; probabilistic methods for evidence integration are attractive in this context as they allow a systematic handling of uncertainty and an elegant way for fusing temporal information. Experiments demonstrate the effectiveness of our approach. We tested this approach successfully on more than 20 testing sequences, with 74 different individuals.</p>}},
  author       = {{Krüger, Volker and Gross, Ralph and Baker, Simon}},
  booktitle    = {{Pattern Recognition : 24th DAGM Symposium Zurich, Switzerland, September 16–18, 2002 Proceedings}},
  isbn         = {{354044209X}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{566--574}},
  publisher    = {{Springer}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{Appearance-based 3-D face recognition from video}},
  url          = {{http://dx.doi.org/10.1007/3-540-45783-6_68}},
  doi          = {{10.1007/3-540-45783-6_68}},
  volume       = {{2449}},
  year         = {{2002}},
}