NDLI: A Novel Model for Independent RBF Neural Networks Employing Gabor-based Kernel PCA with Fractional Power Polynomial Models for Feature Extraction

Content Provider	IEEE Xplore Digital Library
Author	Gaoyun An Qiuqi Ruan Jiying Wu
Copyright Year	2006
Description	Author affiliation: Inst. of Inf. Sci., Beijing Jiaotong Univ. (Gaoyun An)
Abstract	A novel model for independent radial basis function (IRBF) neural network employing Gabor-based kernel PCA with fractional power polynomial models for feature extraction is proposed in this paper. In the new model, a bank of Gabor filters is first built to extract Gabor face representations characterized by selected frequency, locality and orientation to cope with various illuminations, facial expression and poses in face recognition. After extracting Gabor face representations for every face sample, a kernel PCA with fractional power polynomial models is chosen to extract high-order statistical features of extracted Gabor face representations. At last, a new IRBF neural network is built to classify these extracted high-order statistical features of Gabor face representations. According to the experiments on the famous CAS-PEAL face database, our proposed approach could outperform PCA, ICA with architecture II (ICA2) and kernel PCA (KPCA) with standing testing sets proposed in the current release disk of the CAS-PEAL face database
Starting Page	690
Ending Page	695
File Size	5847399
Page Count	6
File Format	PDF
ISBN	1424406048
DOI	10.1109/ICCIAS.2006.294223
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face recognition Neural networks Lighting Feature extraction Frequency Polynomials Spatial databases Gabor filters Kernel Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Gabor-based kernel PCA with fractional power polynomial models for face recognition

Feature extraction using PCA and Kernel-PCA for face recognition

Face recognition base on KPCA with polynomial kernels

Gabor feature based face recognition using kernel methods

Image Recognition Based on Kernel Self-Optimized Learning

Gabor Wavelet Feature Based Face Recognition Using the Fractional Power Polynomial Kernel Fisher Discriminant Model

Independent Component Analysis of Gabor Features for Facial Expression Recognition

Centroid neural network for face recognition

Complete Kernel Fisher discriminant analysis of Gabor features with fractional power polynomial models for face recognition

A Novel Model for Independent RBF Neural Networks Employing Gabor-based Kernel PCA with Fractional Power Polynomial Models for Feature Extraction

Similar Documents

Gabor-based kernel PCA with fractional power polynomial models for face recognition

Feature extraction using PCA and Kernel-PCA for face recognition

Face recognition base on KPCA with polynomial kernels

Gabor feature based face recognition using kernel methods

Image Recognition Based on Kernel Self-Optimized Learning

Gabor Wavelet Feature Based Face Recognition Using the Fractional Power Polynomial Kernel Fisher Discriminant Model

Independent Component Analysis of Gabor Features for Facial Expression Recognition

Centroid neural network for face recognition

Complete Kernel Fisher discriminant analysis of Gabor features with fractional power polynomial models for face recognition

A Novel Model for Independent RBF Neural Networks Employing Gabor-based Kernel PCA with Fractional Power Polynomial Models for Feature Extraction