Name
Abstract | ||
|---|---|---|
3D textures are often described by parametric functions for each pixel, that models the variation in its appearance with respect to varying lighting direction. However, parametric models such as Polynomial Texture Maps (PTMs) tend to smoothen the changes in appearance. We propose a technique to effectively model natural material surfaces and their interactions with changing light conditions. We show that the direct and global components of the image have different nature, and when modeled separately, leads to a more accurate and compact model of the 3D surface texture. For a given lighting position, both components are computed separately and combined to render a new image. This method models sharp shadows and specularities, while preserving the structural relief and surface color. Thus rendered image have enhanced photorealism as compared to images rendered by existing single pixel models such as PTMs. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/WACV.2012.6163034 | Applications of Computer Vision |
Keywords | Field | DocType |
image texture,polynomials,realistic images,3D surface texture,3D texture,component based modeling,lighting direction,parametric functions,parametric models,polynomial texture maps | Texture mapping,Computer vision,Parametric equation,Parametric model,Pattern recognition,Image texture,Computer science,Interpolation,Artificial intelligence,Solid modeling,Pixel,Surface finish | Conference |
ISSN | ISBN | Citations |
1550-5790 E-ISBN : 978-1-4673-0232-6 | 978-1-4673-0232-6 | 2 |
PageRank | References | Authors |
0.35 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Siddharth Kherada | 1 | 2 | 0.35 |
| Prateek Pandey | 2 | 2 | 0.35 |
| Anoop M. Namboodiri | 3 | 255 | 26.36 |