Name
Abstract | ||
|---|---|---|
Procedural textures have been widely used as they can be easily generated from various mathematical models. However, the model parameters are not perceptually meaningful or uniform for non-expert users; therefore it is difficult for general users to obtain a desired texture by tuning the parameters. In order to satisfy users' requirement, we propose a novel procedural texture retrieval scheme that can return textures according to commonly used perceptual dimensions. We establish a procedural texture database that includes abundant textures so as to meet the diverse demands of users. All textures in the database are projected into a perceptual space after we construct the mapping model. First, we investigate the salient features of the input texture; then we calculate the Euclidean distance between the input texture and each texture in the database. Experimental results show that our method can effectively retrieve textures that are perceptually consistent with users' input. |
Year | Venue | Field |
|---|---|---|
2015 | Asia-Pacific Signal and Information Processing Association Annual Summit and Conference | Computer vision,Texture compression,Procedural texture,Pattern recognition,Image texture,Computer science,Visualization,Euclidean distance,Feature extraction,Artificial intelligence,Texture filtering,Salient |
DocType | ISSN | Citations |
Conference | 2309-9402 | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanhai Gan | 1 | 2 | 2.06 |
| Xiaoxu Cai | 2 | 6 | 0.78 |
| Jun Liu | 3 | 0 | 0.68 |
| shengke wang | 4 | 17 | 2.33 |