Name
Abstract | ||
|---|---|---|
A technique to integrate gradient-based and feature-based modules to estimate the optical flow from a pair of images is proposed. The integration strategy is based on a Bayesian approach, where the optical flow is evaluated as the minimizer of a suitable posterior energy function, containing all the gradient and feature information on the problem. The capability of the technique to constrain the displacement in the neighbourhoods of motion discontinuities has been tested. |
Year | Venue | Keywords |
|---|---|---|
1998 | EUSIPCO | gradient methods,image motion analysis,image sequences,integration,bayesian approach,feature-based module,gradient-based module,motion discontinuity,optical flow estimation,posterior energy function,visual module integration,visualization,optical imaging,feature extraction,adaptive optics,image segmentation |
Field | DocType | ISBN |
Computer vision,Classification of discontinuities,Feature detection (computer vision),Visualization,Image segmentation,Feature extraction,Artificial intelligence,Optical flow,Morphological gradient,Mathematics,Adaptive optics | Conference | 978-960-7620-06-4 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luigi Bedini | 1 | 243 | 23.96 |
| andrea cannata | 2 | 1 | 0.37 |
| mario ferraro | 3 | 1 | 0.37 |
| Emanuele Salerno | 4 | 250 | 29.21 |
| Anna Tonazzini | 5 | 382 | 39.07 |