Paper Info
Title
Local Face Recognition Based on the Combination of ICA and NFL
Abstract
This paper presents a local face recognition algorithm that is based on independent component analysis (ICA) and the nearest feature line (NFL). First, we separate a face image into several facial components. Then, we extract feature through combination of principal component analysis (PCA) and ICA; in the step of recognition, we first get each part of distance by NFL, then we calculate the synthetical distance by combining different parts. Compared with holistic image representation, this method has many advantages, such as a much higher recognition rate, more stable and flexible in practice.
Year
DOI
Venue
2004
10.1007/978-3-540-28647-9_155
ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 1
Keywords
Field
DocType
face recognition,principal component analysis,independent component analysis
Facial recognition system,Eigenface,Pattern recognition,Computer science,Image representation,Speech recognition,Artificial intelligence,Independent component analysis,Machine learning,Principal component analysis
Conference
Volume
ISSN
Citations 
3173
0302-9743
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Yisong Ye100.34
Yan Wu2204.50
Mingliang Sun391.05
Mingxi Jin400.68