CFP last date
20 January 2025
Reseach Article

Gender Classification using Geometric Facial Features

by Swathi Kalam, Geetha Guttikonda
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 7
Year of Publication: 2014
Authors: Swathi Kalam, Geetha Guttikonda
10.5120/14855-3222

Swathi Kalam, Geetha Guttikonda . Gender Classification using Geometric Facial Features. International Journal of Computer Applications. 85, 7 ( January 2014), 32-37. DOI=10.5120/14855-3222

@article{ 10.5120/14855-3222,
author = { Swathi Kalam, Geetha Guttikonda },
title = { Gender Classification using Geometric Facial Features },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 7 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number7/14855-3222/ },
doi = { 10.5120/14855-3222 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:52.917060+05:30
%A Swathi Kalam
%A Geetha Guttikonda
%T Gender Classification using Geometric Facial Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 7
%P 32-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Gender classification has become an essential task in human computer interaction (HCI). Gender classification is used in immense number of applications like passive surveillance, control in smart buildings (restricting access to certain areas based on gender) and supermarkets, gender advertising, security investigation. So far detection of gender using facial features is done by using the methods like Gabor wavelets, artificial neural networks and support vector machine. In this work, facial distance measure is used as a progenitor to achieve the gender classification. The proposed approach performs gender classification using mathematical operations on the frontal pose face images using Matlab. This work can be further evaluated in future by using different databases with various poses other than the frontal pose.

References
  1. B. Moghaddam and M. H. Yang, "Gender Classification with Support Vector Machines", Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 306-311, Mar. 2000.
  2. G. Shakhnarovich, P. A. Viola, and B. Moghaddam, "A Unified Learning Framework for Real Time Face Detection and Classification", Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 14-21, 2002.
  3. Ming-Hsuan Yang and Baback Moghaddam, "Support Vector Machines for Visual Gender Classification", Fifteenth International Conference on Pattern Recognition, vol. 1,pp. 5115-5118, 2000.
  4. Baback Moghaddam and Ming-Hsuan, "Learning Gender with Support Faces", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 707-711, May 2002.
  5. Zehang Sun, George Bebis, Xiaoping Yuan, and Sushi J. Louis, "Genetic Feature Subset Selection for Gender Classification": A Comparison Study, IEEE Workshop on Applications of Computer Vision, pp. 165-170, 2002.
  6. Roytatsu Iga, Kyoko Izumi, Hisanori Hayashi, GentaroFukano and Testsuya Ohtani, "Gender and Age Estimation from Face Images", International Conference on The Society of Instrument and Control Engineering, pp. 756-761, August, 2003.
  7. Hui-Cheng Lain and Bao-Liang Lu, "Multi-View Gender Classification using Local Binary Patterns and Support Vector Machines", International Conference on Neural Networks, pp. 202-209, 2006.
  8. Jing Wu, W. A. P. Smith and E. R. Hancock, "Gender Classification using Shape from Shading", International Conference on Image Analysis and Recognition, pp. 925-934, 2008.
  9. ErnoMakinen and Roope Raisamo, "Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 3, pp. 541-547, March 2008.
  10. G. Mallikarjuna Rao, G. R. Babu, G. Vijaya Kumari and N. Krishna Chaitanya, "Methodological Approach for Machine based Expression and Gender Classification, IEEE International Advance Computing Conference", pp. 1369-1374, 6-7 March 2009.
  11. Hui-Cheng Lain and Bao-Liang Lu, "Age Estimation using a Min-Max modular Support Vector Machine", Twelfth International Conference on Neural Information Processing, pp. 83-99,November, 2005.
  12. Rameshk. et. al, "Feature extraction based gender and age estimation" International journal for computer science and Engineering Vol. 02, No. 01s, 2010, 14-23.
  13. V N Prudhvi Raj and Dr T Venkateswarlu, "Denoising of medical ultrasound images using spatial filtering and multiscale Transforms" International Journal of Computer Science & Information Technology Vol 4, No 6, December 2012
Index Terms

Computer Science
Information Sciences

Keywords

Gender classification feature extraction