Name
Abstract | ||
|---|---|---|
We address the problem of dynamic texture (DT) classification using optical flow features. Optical flow based approaches dominate among the currently available DT recognition methods. We introduce rotation- and scale-invariant DT features based on local image distortions computed via optical flow. Then we describe an SVD-based method for measuring the degree of temporal periodicity of a dynamic texture. Finally, we present the results of a DT classification study that compares the performances of different flow features for normal and complete optical flows. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CBMI.2007.385388 | 2007 INTERNATIONAL WORKSHOP ON CONTENT-BASED MULTIMEDIA INDEXING, PROCEEDINGS |
Keywords | Field | DocType |
pattern analysis,optical computing,solid modeling,optical filters,scale invariance,singular value decomposition,optical flow,image classification,image texture,geometrical optics | Singular value decomposition,Computer vision,Pattern recognition,Image texture,Computer science,Optical filter,Solid modeling,Artificial intelligence,Motion analysis,Contextual image classification,Optical flow,Optical computing | Conference |
ISSN | Citations | PageRank |
1949-3983 | 4 | 0.44 |
References | Authors | |
20 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sándor Fazekas | 1 | 242 | 9.74 |
| Chetverikov, D. | 2 | 956 | 99.89 |