Face gender classification based on active appearance model and fuzzy k-nearest neighbors

Len Bui; Dat Tran; Xu Huang; Girija Chetty

Face gender classification based on active appearance model and fuzzy k-nearest neighbors

Len Bui, Dat Tran, Xu Huang, Girija Chetty

Information Systems

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

5 Citations (Scopus)

Abstract

We present a novel method for face gender classification problem. This method employs the powerful Active Appearance Model (AAM) method for modeling human faces and extracting feature vectors, and the simple but powerful Fuzzy k-Nearest Neighbors (Fuzzy k-NN) method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.

Original language	English
Title of host publication	Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2
Editors	Hamid R Arabnia, Leonidas Deligiannidis
Place of Publication	USA
Publisher	CSREA Press
Pages	617-621
Number of pages	5
Volume	2
ISBN (Print)	9781601322232, 1601322240, 1601322259
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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Bui, L., Tran, D., Huang, X., & Chetty, G. (2012). Face gender classification based on active appearance model and fuzzy k-nearest neighbors. In H. R. Arabnia, & L. Deligiannidis (Eds.), Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2 (Vol. 2, pp. 617-621). CSREA Press. http://www.worldcomp-proceedings.com/proc/p2012/IPC4646.pdf

@inproceedings{0f559e49f46d491eab2c3169f6096b77,

title = "Face gender classification based on active appearance model and fuzzy k-nearest neighbors",

abstract = "We present a novel method for face gender classification problem. This method employs the powerful Active Appearance Model (AAM) method for modeling human faces and extracting feature vectors, and the simple but powerful Fuzzy k-Nearest Neighbors (Fuzzy k-NN) method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.",

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

year = "2012",

language = "English",

isbn = "9781601322232",

volume = "2",

pages = "617--621",

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

booktitle = "Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2",

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, Face gender classification based on active appearance model and fuzzy k-nearest neighbors. in HR Arabnia & L Deligiannidis (eds), Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2. vol. 2, CSREA Press, USA, pp. 617-621, 16th International Conference on Image Processing, Computer Vision & Pattern Recognition, Las Vegas, Nevada, United States, 16/07/12. <http://www.worldcomp-proceedings.com/proc/p2012/IPC4646.pdf>

Face gender classification based on active appearance model and fuzzy k-nearest neighbors. / Bui, Len; Tran, Dat ; Huang, Xu et al.
Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2. ed. / Hamid R Arabnia; Leonidas Deligiannidis. Vol. 2 USA: CSREA Press, 2012. p. 617-621.

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

TY - GEN

T1 - Face gender classification based on active appearance model and fuzzy k-nearest neighbors

AU - Bui, Len

AU - Tran, Dat

AU - Huang, Xu

AU - Chetty, Girija

PY - 2012

Y1 - 2012

N2 - We present a novel method for face gender classification problem. This method employs the powerful Active Appearance Model (AAM) method for modeling human faces and extracting feature vectors, and the simple but powerful Fuzzy k-Nearest Neighbors (Fuzzy k-NN) method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.

AB - We present a novel method for face gender classification problem. This method employs the powerful Active Appearance Model (AAM) method for modeling human faces and extracting feature vectors, and the simple but powerful Fuzzy k-Nearest Neighbors (Fuzzy k-NN) method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.

M3 - Conference contribution

SN - 9781601322232

SN - 1601322240

SN - 1601322259

VL - 2

SP - 617

EP - 621

BT - Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2

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 -

Face gender classification based on active appearance model and fuzzy k-nearest neighbors

Abstract

Conference

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