A new Approach to Bayesian Method for Face Recognition

Len Bui; Dat Tran; Xu Huang; Girija Chetty

A new Approach to Bayesian Method for Face Recognition

Len Bui
, Dat Tran
, Xu Huang
, Girija Chetty

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

Abstract

In this paper, we propose a new approach to Bayesian subspace method for face recognition. We review this method and point out some weak points in its assumptions and propose a practical solution to overcome those weak points. In addition, we present an efficient way to estimate the high dimensional Gaussian density function.

Original language	English
Title of host publication	Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12
Editors	Hamid R Arabnia, Leonidas Deligiannidis
Place of Publication	USA
Publisher	CSREA Press
Pages	547-553
Number of pages	7
Volume	1
ISBN (Print)	9781601322232, 9781601322259
Publication status	Published - 2012
Event	16th International Conference on Image Processing, Computer Vision & Pattern Recognition - Las Vegas, Las Vegas, United States Duration: 16 Jul 2012 → 19 Jul 2012 https://worldacademyofscience.org/worldcomp12/ws/conferences/ipcv12/General%20Information.html

Conference

Conference	16th International Conference on Image Processing, Computer Vision & Pattern Recognition
Abbreviated title	IPCV 2012
Country/Territory	United States
City	Las Vegas
Period	16/07/12 → 19/07/12
Internet address	https://worldacademyofscience.org/worldcomp12/ws/conferences/ipcv12/General%20Information.html

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@inproceedings{77105e21c78a439ebbfaa522c2a43189,

title = "A new Approach to Bayesian Method for Face Recognition",

abstract = "In this paper, we propose a new approach to Bayesian subspace method for face recognition. We review this method and point out some weak points in its assumptions and propose a practical solution to overcome those weak points. In addition, we present an efficient way to estimate the high dimensional Gaussian density function.",

author = "Len Bui and Dat Tran and Xu Huang and Girija Chetty",

year = "2012",

language = "English",

isbn = "9781601322232",

volume = "1",

pages = "547--553",

editor = "Arabnia, \{Hamid R\} and Leonidas Deligiannidis",

booktitle = "Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12",

publisher = "CSREA Press",

note = "16th International Conference on Image Processing, Computer Vision \& Pattern Recognition, IPCV 2012 ; Conference date: 16-07-2012 Through 19-07-2012",

url = "https://worldacademyofscience.org/worldcomp12/ws/conferences/ipcv12/General\%20Information.html",

}

Bui, L, Tran, D, Huang, X & Chetty, G 2012, A new Approach to Bayesian Method for Face Recognition. in HR Arabnia & L Deligiannidis (eds), Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12. vol. 1, CSREA Press, USA, pp. 547-553, 16th International Conference on Image Processing, Computer Vision & Pattern Recognition, Las Vegas, Nevada, United States, 16/07/12. <http://worldcomp-proceedings.com/proc/p2012/IPC4645.pdf>

A new Approach to Bayesian Method for Face Recognition. / Bui, Len; Tran, Dat; Huang, Xu et al.
Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12. ed. / Hamid R Arabnia; Leonidas Deligiannidis. Vol. 1 USA: CSREA Press, 2012. p. 547-553.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - A new Approach to Bayesian Method for Face Recognition

AU - Bui, Len

AU - Tran, Dat

AU - Huang, Xu

AU - Chetty, Girija

PY - 2012

Y1 - 2012

N2 - In this paper, we propose a new approach to Bayesian subspace method for face recognition. We review this method and point out some weak points in its assumptions and propose a practical solution to overcome those weak points. In addition, we present an efficient way to estimate the high dimensional Gaussian density function.

AB - In this paper, we propose a new approach to Bayesian subspace method for face recognition. We review this method and point out some weak points in its assumptions and propose a practical solution to overcome those weak points. In addition, we present an efficient way to estimate the high dimensional Gaussian density function.

M3 - Conference contribution

SN - 9781601322232

SN - 9781601322259

VL - 1

SP - 547

EP - 553

BT - Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12

A2 - Arabnia, Hamid R

A2 - Deligiannidis, Leonidas

PB - CSREA Press

CY - USA

T2 - 16th International Conference on Image Processing, Computer Vision & Pattern Recognition

Y2 - 16 July 2012 through 19 July 2012

ER -

A new Approach to Bayesian Method for Face Recognition

Abstract

Conference

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