Name
Abstract | ||
|---|---|---|
In this paper, we suggest a viewpoint-invariant face recognition model based on view-based representation. The suggested model has four stages: view-based representation, viewpoint classification, frontal face estimation and face recognition. For view-based representation, we obtained the feature space by using independent subspace analysis, the bases of which are grouped like the neurons in the brain's visual area. The viewpoint of a facial image can be easily classified by a single-layer perceptron due to viewdependent activation characteristic of the feature space. To estimate the independent subspace analysis representation of frontal face, a radial basis neural network learns to generalize the relation of the bases between two viewpoints. Face recognition relies on a normalized correlation for selecting the most similar frontal faces in a gallery. Through our face recognition experiment on XM2VTS [9], we obtained a face recognition rate of 89.33%. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-37275-2_109 | ICIC (2) |
Keywords | Field | DocType |
face recognition,feature space,neural network | Computer science,Image processing,Artificial intelligence,Artificial neural network,Computer vision,Facial recognition system,Feature vector,Three-dimensional face recognition,Subspace topology,Pattern recognition,Invariant (mathematics),Perceptron,Machine learning | Conference |
Volume | ISSN | ISBN |
4114 | 0302-9743 | 3-540-37274-1 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinyun Chung | 1 | 2 | 1.11 |
| Juho Lee | 2 | 0 | 0.34 |
| Hyun-jin Park | 3 | 48 | 9.56 |
| Hyun Seung Yang | 4 | 200 | 34.21 |