Name
Abstract | ||
|---|---|---|
In this paper, we propose a face recognition method called the commonface by using the common vector approach. A face image is regarded as a summation of a common vector which represents the invariant properties of the corresponding face class, and a difference vector which presents the specific properties of the corresponding face image such as face appearance, pose and expression. Thus, by deriving the common vector of each face class, the common feature of each person is obtained which removes the differences of face images belonging to the same person. For test face image, the remaining vector with each face class is derived with the similar procedure to the common vector, which is then compared with the common vector of each face class to predict the class label of query face by finding the minimum distance between the remaining vector and the common vector. Furthermore, we extend the common vector approach (CVP) to kernel CVP to improve the performance of CVP. The experimental results suggest that the proposed commonface approach provides a better representation of individual common feature and achieves lower error rates in face recognition. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.patcog.2006.04.037 | Pattern Recognition |
Keywords | Field | DocType |
Face recognition,Common vector approach,Kernel method | Kernel (linear algebra),Computer vision,Facial recognition system,Pattern recognition,Artificial intelligence,Invariant (mathematics),Kernel method,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 11 | 0031-3203 |
Citations | PageRank | References |
6 | 0.49 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunhui He | 1 | 9 | 2.45 |
| Li Zhao | 2 | 380 | 27.36 |
| Cairong Zou | 3 | 415 | 27.19 |