Name
Abstract | ||
|---|---|---|
Caricature is affected strongly by the attribute relationship between input face and mean face. This paper proposes a method of facial attribute classification by means of the statistics of many mean faces and an input face. These processes are made up by the estimation function of the input face and the attribute matrix which is defined by the distances of all feature points of the face and its variances. There should be many attribute matrices characterized by the different age and different gender sets of faces. This proposal delivered the expected results enough for the automation of the mean face selection and clarification as the new caricature generation principle. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-45226-3_119 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
matrices,modeling | Pattern recognition,Matrix (mathematics),Computer science,Automation,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
2774 | 0302-9743 | 5 |
PageRank | References | Authors |
0.60 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takayuki Fujiwara | 1 | 51 | 14.13 |
| Hiroyasu Koshimizu | 2 | 100 | 31.83 |