Name
Abstract | ||
|---|---|---|
We develop a novel approach to face verification based on the Error Correct- ing Output Coding (ECOC) classifier design concept. In the training phase the client set is repeatedly divided into two ECOC specified sub-sets (super- classes) to train a set of binary classifiers. The output of the classifiers defines the ECOC feature space, in which it is easier to separate transformed patterns representing clients and impostors. The proposed method exhibits superior verification performance on the well known XM2VTS data set as compared with previously reported results. |
Year | Venue | Keywords |
|---|---|---|
2001 | BMVC | error correction,feature space |
DocType | Citations | PageRank |
Conference | 6 | 1.05 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Kittler | 1 | 14346 | 1465.03 |
| Reza Ghaderi | 2 | 199 | 14.97 |
| Terry Windeatt | 3 | 501 | 44.59 |
| Jiri Matas | 4 | 335 | 35.85 |