Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407934 | Neurocomputing | 2013 | 11 Pages |
Abstract
Sparse representation has received an increasing amount of interest in recent years. By representing the testing image as a sparse linear combination of the training samples, sparse representation based classification (SRC) has been successfully applied in face recognition. In SRC, the ℓ1 minimization instead of the ℓ0 minimization is used to seek for the sparse solution for its computational convenience and efficiency. However, ℓ1 minimization does not always yield sufficiently sparse solution in many practical applications. In this paper, we propose a novel SRC method, namely the ℓp (0
► Sparse representation based classification via ℓp (0
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Song Guo, Zhan Wang, Qiuqi Ruan,