Name
Abstract | ||
|---|---|---|
A new unsupervised approach to face recognition is proposed in this paper. Shape and color entropy is presented to descript face features. Firstly, images are pre-processed including face normalization and image segmentation and so on. Secondly, by using the information entropy theory, the method defines the color and shape entropy of the face images, respectively. Finally, an integrated similarity measurement framework is presented by computing mutual information between images according to these entropies. Compared with other methods of feature description, experiments indicate that this approach is more effective and efficient. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-87442-3_13 | ICIC (1) |
Keywords | Field | DocType |
face image,face feature,face recognition,mutual information,shape entropy,new unsupervised approach,information entropy theory,feature description,face normalization,color entropy,image segmentation,information entropy | Facial recognition system,Computer vision,Normalization (statistics),Pattern recognition,Computer science,Image segmentation,Artificial intelligence,Mutual information,Feature description,Entropy (information theory),Machine learning | Conference |
Volume | ISSN | Citations |
5226 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 11 | 2 |