Title :
Classification-based face detection using Gabor filter features
Author :
Huang, Lin-Lin ; Shimizu, Akinobu ; Kobatake, Hidefumi
Author_Institution :
Graduate Sch. of Bio-Applications & Syst. Eng., Tokyo Univ. of Agric. & Technol., Japan
Abstract :
This work proposes a classification-based face detection method using Gabor filter features. Considering the desirable characteristics of spatial locality and orientation selectivities of the Gabor filter, we design four filters for extracting facial features from the local image. The feature vector based on Gabor filters is used as the input of the classifier, which is a polynomial neural network (PNN) on a reduced feature subspace learned by principal component analysis (PCA). The effectiveness of the proposed method is demonstrated by the experimental results on testing a large number of images and the comparison with the state-of-the-art method.
Keywords :
feature extraction; filtering theory; neural nets; principal component analysis; Gabor filter features; PCA; PNN; classification-based face detection; facial features extraction; orientation selectivities; polynomial neural network; principal component analysis; reduced feature subspace; spatial locality; Face detection; Face recognition; Facial features; Feature extraction; Gabor filters; Neural networks; Polynomials; Principal component analysis; Robustness; Testing;
Conference_Titel :
Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on
Print_ISBN :
0-7695-2122-3
DOI :
10.1109/AFGR.2004.1301565