Hybrid independent component analysis and support vector machine learning scheme for face detection

Authors:
Yuan Qi;D. Doermann;D. DeMenthon
Affiliations:
Lab. for Language & Media Process., Maryland Univ., College Park, MD, USA;-;-
Venue:
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Year:
2001

Citing 0
Cited 5

Face Detection Based on Support Vector Machines

SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Applications of Support Vector Machines for Pattern Recognition: A Survey

SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Automated facial expression recognition – an integrated approach with optical flow analysis and Support Vector Machines

International Journal of Intelligent Systems Technologies and Applications
Face detection and facial component extraction by wavelet decomposition and support vector machines

AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Sketch case based spatial topological data retrieval

PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

We propose a new hybrid unsupervised/supervised learning scheme that integrates independent component analysis (ICA) with the support vector machine (SVM) approach and apply this new learning scheme to the face detection problem. In low-level feature extraction, ICA produces independent image bases that emphasize edge information in the image data. In high-level classification, SVM classifies the ICA features as a face or non-faces. Our experimental results show that by using ICA features we obtain a larger margin of separation and fewer support vectors than by training SVM directly on the image data. This indicates better generalization performance, which is verified in our experiments.