Name
Abstract | ||
|---|---|---|
This paper proposes a method of synthesizing a high-resolution facial image from a low-resolution facial image based on top-down learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in an given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be synthesized by using the optimal coefficients for linear combination of the high-resolution prototypes. The encouraging results of the proposed method show that our method can be used to increase the performance of the face recognition by applying our method to enhance the low-resolution facial images captured at surveillance systems. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-44887-X_45 | AVBPA |
Keywords | Field | DocType |
high-resolution prototype,linear combination,texture information,top-down learning,face recognition,high-resolution facial image,encouraging result,optimal coefficient,low-resolution facial image,square minimization,proposed method show,top down,high resolution,low resolution,least square | Computer vision,Linear combination,Facial recognition system,Face hallucination,Computer science,Image texture,Bicubic interpolation,Pixel,Artificial intelligence,Biometrics,Image resolution | Conference |
Volume | ISSN | ISBN |
2688 | 0302-9743 | 3-540-40302-7 |
Citations | PageRank | References |
2 | 0.56 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bon-Woo Hwang | 1 | 177 | 16.33 |
| Jeong-seon Park | 2 | 202 | 18.13 |
| Seong-Whan Lee | 3 | 3756 | 343.90 |