Name
Abstract | ||
|---|---|---|
In this paper, we present a local appearance-based approach for 3-D face recognition. In the proposed algorithm, we first register the 3-D point clouds to provide a dense correspondence between faces. Afterwards, we analyze two mapping techniques-the closest-point mapping and the ray-casting mapping, to construct depth images from the corresponding well-registered point clouds. The depth images that are obtained are then divided into local regions where the discrete cosine transformation is performed to extract local information. The local features are combined at the feature level for classification. Experimental results on the FRGC version 2.0 face database show that the proposed algorithm performs superior to the well-known face recognition algorithms. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TIFS.2007.902924 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
local appearance-based approach,local information,3-d face recognition.,index terms—automatic registration,ray-casting mapping,local appearance-based models,depth image,proposed algorithm,local feature,local appearance face recognition,face database show,3-d face recognition,mapping techniques-the closest-point mapping,local region,face recognition,discrete cosine transform,point cloud,feature extraction,ray casting,biometrics,image classification,meteorology,indexing terms | Facial recognition system,Computer vision,Pattern recognition,Computer science,Appearance based,Feature extraction,Artificial intelligence,Biometrics,Contextual image classification,Point cloud,Discrete cosine transforms,Discrete cosine transformation | Journal |
Volume | Issue | ISSN |
2 | 3 | 1556-6013 |
Citations | PageRank | References |
5 | 0.52 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| H. K. Ekenel | 1 | 98 | 8.69 |
| Hua Gao | 2 | 5 | 0.52 |
| Rainer Stiefelhagen | 3 | 3512 | 274.86 |