An Automatic Face Detection and Gender Classification from Color Images using Support Vector Machine

This paper presents combined face detection and gender classification method of discriminating between faces of men and women. This is done by detecting the human face area in image given and detecting facial features based on the measurements in pixels. The proposed algorithm converts the RGB image into the YCbCr color space to detect the skin regions from the facial image. But in order to detect facial features the color image is converted into gray scale image. This paper presents appearance-based approach with Gabor filter and Support Vector Machine (SVM) classifier. Gabor filter banks are used to extract important facial features, SVM classifier is then used to recognize the facial features. It is proved that SVM can provide superior performance. Different kernel functions have been useful in cases where the data are not linearly separable. These kernel functions transform data to higher dimensional space where they can be separated easily.

[1]  Modesto Castrillón Santana,et al.  An Analysis of Automatic Gender Classification , 2007, CIARP.

[2]  Shinichi Tamura,et al.  Male/female identification from 8×6 very low resolution face images by neural network , 1996, Pattern Recognit..

[3]  Roope Raisamo,et al.  An experimental comparison of gender classification methods , 2008, Pattern Recognit. Lett..

[4]  Harry Wechsler,et al.  The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..

[5]  Mircea Nicolescu,et al.  Feature Fusion Hierarchies for gender classification , 2008, 2008 19th International Conference on Pattern Recognition.

[6]  Paul A. Viola,et al.  A unified learning framework for real time face detection and classification , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[7]  Neil Davey,et al.  Gender Classification of Face Images: The Role of Global and Feature-Based Information , 2004, ICONIP.

[8]  A. Martínez,et al.  The AR face databasae , 1998 .

[9]  Michael J. Lyons,et al.  Classifying facial attributes using a 2-D Gabor wavelet representation and discriminant analysis , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[10]  Ming-Hsuan Yang,et al.  Learning Gender with Support Faces , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Shumeet Baluja,et al.  Boosting Sex Identification Performance , 2005, International Journal of Computer Vision.

[12]  Terrence J. Sejnowski,et al.  SEXNET: A Neural Network Identifies Sex From Human Faces , 1990, NIPS.

[13]  Ming-Hsuan Yang,et al.  Gender classification with support vector machines , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[14]  Harry Wechsler,et al.  Gender and ethnic classification of face images , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[15]  Aleix M. Martinez,et al.  The AR face database , 1998 .

[16]  Jean-Luc Dugelay,et al.  Facial gender recognition using multiple sources of visual information , 2008, 2008 IEEE 10th Workshop on Multimedia Signal Processing.

[17]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.