NDLI: One sample per person face recognition based on particle swarm optimisation

Content Provider	IET Digital Library
Author	Zhang, Yan Peng, Hua
Abstract	One sample per person face recognition problem is a challenging problem in face recognition. The authors propose a basis plus variety model on a high-dimensional unit sphere to tackle the problem. In the model, the query image is approximately a linear combination of the basis image and variety image. The basis images are the neutral images of subjects and variety images are generalised from multi-sample subjects in the gallery. Particle swarm optimisation is chosen to find out the optimum combination of the basis and variety in terms of the minimum L2 distance relative to the query image. The identity of the query image is equal to the identity of the basis image of the optimum combination. Experiments on the extended Yale face database B and AR database are provided to show the validity of the proposed algorithm.
Starting Page	100
Ending Page	105
Page Count	6
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 2, Apr (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2015.0213
Journal	IET Signal Processing
Publisher Date	2016-04-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AR Database Basis Image Basis Plus Variety Model Computer Vision And Image Processing Technique Extended Yale Face Database B Face Recognition Image Recognition Image Retrieval Multisample Subject Neutral Image One Sample Per Person Face Recognition Optimisation Technique OSPP Particle Swarm Optimisation Query Image Identification Variety Image
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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