Name
Abstract | ||
|---|---|---|
Online contour-based tracking is considered through the estimation perspective. We propose a recursive dynamic filtering solution to the tracking problem. The state of the target is described by a pose state which represents the ensemble movement and a shape state which represents the local deformations. The shape state of the filter is described implicitly by a probability field with prediction and correction mechanisms expressed accordingly. The filtering procedure decouples the pose and shape estimation. Experiments conducted with objective measures of quality demonstrate improved tracking. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICIP.2009.5414413 | Image Processing |
Keywords | Field | DocType |
ensemble movement,shape estimation,online contour-based tracking,objective measure,estimation perspective,tracking problem,probabilistic shape filter,correction mechanism,shape state,online contour tracking,local deformation,probability field,pose estimation,kalman filters,tracking,bayesian methods,shape,probability,visual tracking | Computer vision,Pattern recognition,Computer science,Image representation,Filter (signal processing),Kalman filter,Pose,Artificial intelligence,Probabilistic logic,Filtering theory,Recursion,Bayesian probability | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-5655-0 | 978-1-4244-5655-0 | 1 |
PageRank | References | Authors |
0.37 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibrahima J. Ndiour | 1 | 21 | 3.44 |
| Omar Arif | 2 | 22 | 5.87 |
| Jochen Teizer | 3 | 90 | 11.30 |
| Patricio A Vela | 4 | 369 | 39.12 |