Gender classification with support vector machines

Details Gender classification with support vector machines Gender classification with support vector machines

2006-01-24

2006-01-24

Wu, Jingge (Department: 2723)

Image analysis

Applications

Personnel identification

C382S159000

Reexamination Certificate

active

06990217

ABSTRACT:
A method classifies images of faces according to gender. Training images of male and female faces are supplied to a vector support machine. A small number of support vectors are determined from the training images. The support vectors identify a hyperplane. After training, a test image is supplied to the support vector machine. The test image is classified according to the gender of the test image with respect to the hyperplane.

REFERENCES:
patent: 5710833 (1998-01-01), Moghaddam et al.
Osuna et al. Training Support Vector Machines: An Application to Face Detection. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Jun., 1997. 130-136.
Gutta et al. Gender Classification of Human Faces Using Hybrid Classifier Systems. IEEE International Conference on Neural Networks. Jun., 1997. vol. 3, 1353-1358.
Brunelli et al.; “HyberBF Networks for Gender Classification”; InProceedings of the Image Understanding Workshop, DARPA, San Diego, pp. 311-314, 1992.
Cottrell et al., “EMPATH: Face, Emotion and Gender Recognition Using Holons”; InAdvances in Neural Information Processing Systems, pp. 564-571, 1993.
Edelman et al.; “Sex Classification of Face Areas: How Well Can A Linear Neural Network Predict Human Performance?”; Journal of Bilogical Systems, 6(3): 241-264, 1998.
Golomb et al., “Sexnet: A Neural Network Identifies Sex from Human Faces”; InAdvances in Neural Information Processing Systems(NIPS), vol. 3, Lippmann et al. (Eds.), Morgan Kaufmann, 1990, pp. 572-577.
Gutta et al., “Gender and Ethnic Classification of Face Images”; In Proceedings of the IEEE International Automatic Face and Gesture Recognition, pp. 194-199, 1998.
Hill et al.; “Perceiving the Sex & Race of Faces: The Role of Shape and Colour”; Proc. R. Soc. Lond. B (1995) 261, pp. 367-373.
O'Toole et al.; “The Perception of Face Gender: The Role of Stimulus Structure in Recognition and Classification”;Memory and Recognition, vol. 25, 1997.
Sim et al.; “High-Performance Memory-based Face Recognition for Visitor Identification”; 1999.
Tamura et al.; “Male/Female Identification from 8x6 Very Low Resolution Face Images by Neural Network”;Pattern Recognition29(2): pp. 331-335, 1996.
Wiskott et al.; “Face Recognition and Gender Determination”;Proc. Intl. Workshop on Automatic Face and Gender Recognition, pp. 92-97, 1995.

Affiliated with

Also associated with

Rating

Gender classification with support vector machines does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Gender classification with support vector machines, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Gender classification with support vector machines will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3552005