Name
Abstract | ||
|---|---|---|
PCA and NMF subspace approaches have become the most representative methods in face recognition, which act in the similar way as a neural network auto-associative memory. By integrating with LDA subspace, in this paper, two subspace associative memories, PCALDA and NMFLDA, are proposed, and how they recognize the partially damaged faces is presented. The theoretical expressions are plotted, and the comparative experiments are completed for the UMIST face database. It shows that NMFLDA subspace associative memory outperform PCALDA subspace method significantly in recognizing partially damaged faces. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11760023_8 | ISNN (2) |
Keywords | Field | DocType |
neural network auto-associative memory,pcalda subspace method,subspace auto-associative memory,face recognition,lda subspace,comparative experiment,facial image,subspace associative memory,nmf subspace approach,nmflda subspace associative memory,representative method,umist face database,associative memory,neural network | Facial recognition system,Associative property,Content-addressable memory,Expression (mathematics),Subspace topology,Pattern recognition,Computer science,Artificial intelligence,Non-negative matrix factorization,Linear discriminant analysis,Artificial neural network | Conference |
Volume | ISSN | ISBN |
3972 | 0302-9743 | 3-540-34437-3 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaorong Pu | 1 | 85 | 11.17 |
| Zhang Yi | 2 | 1765 | 194.41 |
| Y. Wu | 3 | 1178 | 139.36 |