Investigating the boosting framework for face recognition

B.J. Boom; R.T.A. van Rootseler

Investigating the boosting framework for face recognition

B.J. Boom, R.T.A. van Rootseler

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

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Abstract

The boosting framework has shown good performance in face recognition. By combining a set of features with Adaboost, a similarity function is developed which determines if a pair of face images belongs to the same person or not. Recently, many features have been used in combination with Adaboost, achieving good results on the FERET database. In this paper we compare the results of several features on the same database and discuss our solutions on some of the open issues in this method. We compare the boosting framework with some standard algorithms and test the boosting algorithm under difficult circumstances, like illumination and registration noise.

Original language	Undefined
Title of host publication	Proceedings of the 28th Symposium on Information Theory in the Benelux
Editors	Raymond N.J. Veldhuis, R.N.J. Veldhuis, H.S. Cronie
Place of Publication	Eindhoven
Publisher	Werkgemeenschap voro Informatie- en Communicatietechniek
Pages	189-196
Number of pages	8
ISBN (Print)	978-90-365-2509-1
Publication status	Published - 24 May 2007
Event	28th Symposium on Information Theory in the Benelux 2007 - Best Western Dish Hotel, Enschede, Netherlands Duration: 24 May 2007 → 25 May 2007 Conference number: 28

Publication series

Name
Publisher	Werkgemeenschap voor Informatie- en Communicatietechniek
Number	LNCS4549

Conference

Conference	28th Symposium on Information Theory in the Benelux 2007
Country/Territory	Netherlands
City	Enschede
Period	24/05/07 → 25/05/07

Keywords

SCS-Safety
METIS-241829
EWI-10852
IR-64276

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Cite this

@inproceedings{d33fc87375d6427ca5a12d4d2f67b73d,

title = "Investigating the boosting framework for face recognition",

abstract = "The boosting framework has shown good performance in face recognition. By combining a set of features with Adaboost, a similarity function is developed which determines if a pair of face images belongs to the same person or not. Recently, many features have been used in combination with Adaboost, achieving good results on the FERET database. In this paper we compare the results of several features on the same database and discuss our solutions on some of the open issues in this method. We compare the boosting framework with some standard algorithms and test the boosting algorithm under difficult circumstances, like illumination and registration noise.",

keywords = "SCS-Safety, METIS-241829, EWI-10852, IR-64276",

author = "B.J. Boom and {van Rootseler}, R.T.A.",

year = "2007",

month = may,

day = "24",

language = "Undefined",

isbn = "978-90-365-2509-1",

publisher = "Werkgemeenschap voro Informatie- en Communicatietechniek",

number = "LNCS4549",

pages = "189--196",

editor = "Veldhuis, {Raymond N.J.} and R.N.J. Veldhuis and H.S. Cronie",

booktitle = "Proceedings of the 28th Symposium on Information Theory in the Benelux",

note = "null ; Conference date: 24-05-2007 Through 25-05-2007",

}

Boom, BJ & van Rootseler, RTA 2007, Investigating the boosting framework for face recognition. in RNJ Veldhuis, RNJ Veldhuis & HS Cronie (eds), Proceedings of the 28th Symposium on Information Theory in the Benelux. Werkgemeenschap voro Informatie- en Communicatietechniek, Eindhoven, pp. 189-196, 28th Symposium on Information Theory in the Benelux 2007, Enschede, Netherlands, 24/05/07.

Investigating the boosting framework for face recognition. / Boom, B.J.; van Rootseler, R.T.A.

Proceedings of the 28th Symposium on Information Theory in the Benelux. ed. / Raymond N.J. Veldhuis; R.N.J. Veldhuis; H.S. Cronie. Eindhoven : Werkgemeenschap voro Informatie- en Communicatietechniek, 2007. p. 189-196.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

TY - GEN

T1 - Investigating the boosting framework for face recognition

AU - Boom, B.J.

AU - van Rootseler, R.T.A.

N1 - Conference code: 28

PY - 2007/5/24

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N2 - The boosting framework has shown good performance in face recognition. By combining a set of features with Adaboost, a similarity function is developed which determines if a pair of face images belongs to the same person or not. Recently, many features have been used in combination with Adaboost, achieving good results on the FERET database. In this paper we compare the results of several features on the same database and discuss our solutions on some of the open issues in this method. We compare the boosting framework with some standard algorithms and test the boosting algorithm under difficult circumstances, like illumination and registration noise.

AB - The boosting framework has shown good performance in face recognition. By combining a set of features with Adaboost, a similarity function is developed which determines if a pair of face images belongs to the same person or not. Recently, many features have been used in combination with Adaboost, achieving good results on the FERET database. In this paper we compare the results of several features on the same database and discuss our solutions on some of the open issues in this method. We compare the boosting framework with some standard algorithms and test the boosting algorithm under difficult circumstances, like illumination and registration noise.

KW - SCS-Safety

KW - METIS-241829

KW - EWI-10852

KW - IR-64276

M3 - Conference contribution

SN - 978-90-365-2509-1

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EP - 196

BT - Proceedings of the 28th Symposium on Information Theory in the Benelux

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A2 - Veldhuis, R.N.J.

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CY - Eindhoven

Y2 - 24 May 2007 through 25 May 2007

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