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

Len Bui, Dat Tran, Xu Huang, Girija Chetty

Research output: A Conference proceeding or a Chapter in BookConference contribution

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 languageEnglish
Title of host publicationProceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2
EditorsHamid R Arabnia, Leonidas Deligiannidis
Place of PublicationUSA
PublisherCSREA Press
Pages617-621
Number of pages5
Volume2
ISBN (Print)9781601322232, 1601322240, 1601322259
Publication statusPublished - 2012
Event16th International Conference on Image Processing, Computer Vision & Pattern Recognition - Las Vegas, Las Vegas, United States
Duration: 16 Jul 201219 Jul 2012
https://worldacademyofscience.org/worldcomp12/ws/conferences/ipcv12/General%20Information.html

Conference

Conference16th International Conference on Image Processing, Computer Vision & Pattern Recognition
Abbreviated titleIPCV 2012
CountryUnited States
CityLas Vegas
Period16/07/1219/07/12
Internet address

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Experiments

Cite this

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). USA: CSREA Press.
Bui, Len ; Tran, Dat ; Huang, Xu ; Chetty, Girija. / Face gender classification based on active appearance model and fuzzy k-nearest neighbors. Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2. editor / Hamid R Arabnia ; Leonidas Deligiannidis. Vol. 2 USA : CSREA Press, 2012. pp. 617-621
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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",
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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 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, United States, 16/07/12.

Face gender classification based on active appearance model and fuzzy k-nearest neighbors. / Bui, Len; Tran, Dat; Huang, Xu; Chetty, Girija.

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 BookConference contribution

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

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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

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

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Bui L, Tran D, Huang X, Chetty G. Face gender classification based on active appearance model and fuzzy k-nearest neighbors. In Arabnia HR, Deligiannidis L, editors, Proceedings Of The 2012 International Conference On Image Processing, Computer Vision, & Pattern Recognition (IPVC 2012) : Vol. 2. Vol. 2. USA: CSREA Press. 2012. p. 617-621