Name
Abstract | ||
|---|---|---|
Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) under the proposed framework. Different from previous cross-view methods only preserving inter-view discriminant information or the intra-view local structure, CLODA preserves the local structure and the discriminant information of both intra-view and inter-view. Extensive experiments are conducted to evaluate our algorithms on two cross-view face recognition problems: face recognition across poses and face recognition across resolutions. These real-world face recognition experiments demonstrate that our framework achieves impressive performance in the cross-view problems. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-37444-9_60 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
cross-view matching problem,face recognition,proposed framework,cross-view method,cross-view graph embedding,general framework,cross-view problem,traditional cross-view method,new cross-view method,cross-view face recognition problem,previous cross-view method | Computer vision,Facial recognition system,Pattern recognition,Canonical correlation,Graph embedding,Discriminant,Computer science,Local structure,Artificial intelligence,Linear discriminant analysis,Machine learning | Conference |
Volume | Issue | ISSN |
7725 LNCS | PART 2 | 16113349 |
Citations | PageRank | References |
3 | 0.45 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwu Huang | 1 | 252 | 15.26 |
| Shiguang Shan | 2 | 6322 | 283.75 |
| Haihong Zhang | 3 | 348 | 9.17 |
| Shihong Lao | 4 | 2005 | 118.22 |
| Xilin Chen | 5 | 6291 | 306.27 |