Name
Abstract | ||
|---|---|---|
We propose a novel stochastic generative parametric freckle model for the analysis and synthesis of human faces. Morphable Models are the state-of-the-art generative parametric face models. However, they are unable to synthesize freckles which are part of atural face variation. The deficiency lies in requiring point-to-point correspondence on the texture pixels. We propose to assume a correspondence between freckle density and not the freckles themselves. We propose a model that is stochastic, generative, and parametric and generates freckles with a point process according to a density and size distribution. The resulting model can synthesize photo-realistic freckles according to observations as well as add freckles to existing faces. We create more realistic faces than with Morphable Models alone and allow for detailed face pigment analysis. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/FG.2018.00069 | 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) |
Keywords | Field | DocType |
face synthesis,morphable model,freckle synthesis | Pattern recognition,Face synthesis,Computer science,Point process,Parametric statistics,Artificial intelligence,Pixel,Freckle | Conference |
ISSN | ISBN | Citations |
2326-5396 | 978-1-5386-2336-7 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreas Schneider | 1 | 14 | 4.05 |
| Bernhard Egger | 2 | 37 | 3.78 |
| Thomas Vetter | 3 | 4528 | 529.79 |