Title
Using the idea of the sparse representation to perform coarse-to-fine face recognition
Abstract
In this paper, we propose a coarse-to-fine face recognition method. This method consists of two stages and works in a similar way as the well-known sparse representation method. The first stage determines a linear combination of all the training samples that is approximately equal to the test sample. This stage exploits the determined linear combination to coarsely determine candidate class labels of the test sample. The second stage again determines a weighted sum of all the training samples from the candidate classes that is approximately equal to the test sample and uses the weighted sum to perform classification. The rationale of the proposed method is as follows: the first stage identifies the classes that are ''far'' from the test sample and removes them from the set of the training samples. Then the method will assign the test sample into one of the remaining classes and the classification problem becomes a simpler one with fewer classes. The proposed method not only has a high accuracy but also can be clearly interpreted.
Year
DOI
Venue
2013
10.1016/j.ins.2013.02.051
Inf. Sci.
Keywords
Field
DocType
Biometrics,Security access,Face recognition,Information fusion,Decision making
Facial recognition system,Linear combination,Computer science,Sparse approximation,Algorithm,Artificial intelligence,Biometrics,Information fusion,Machine learning
Journal
Volume
ISSN
Citations 
238,
0020-0255
57
PageRank 
References 
Authors
1.17
44
6
Name
Order
Citations
PageRank
Xu Yong1211973.51
Qi Zhu272760.59
Zizhu Fan332914.61
David Zhang47365360.85
Jian-Xun Mi51629.79
Zhihui Lai6120476.03