Name
Title | ||
|---|---|---|
Robust tracking of unknown objects through adaptive size estimation and appearance learning |
Abstract | ||
|---|---|---|
This work employs an adaptive learning mechanism to perform tracking of an unknown object through RGBD cameras. We extend our previous framework to robustly track a wider range of arbitrarily shaped objects by adapting the model to the measured object size. The size is estimated as the object undergoes motion, which is done by fitting an inscribed cuboid to the measurements. The region spanned by this cuboid is used during tracking, to determine whether or not new measurements should be added to the object model. In our experiments we test our tracker with a set of objects of arbitrary shape and we show the benefit of the proposed model due to its ability to adapt to the object shape which leads to more robust tracking results. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICRA.2016.7487179 | 2016 IEEE International Conference on Robotics and Automation (ICRA) |
Keywords | Field | DocType |
robust object tracking,adaptive size estimation,appearance learning,adaptive learning mechanism,RGBD cameras,red-green-blue-depth cameras,object motion,inscribed cuboid,arbitrary shape object | Computer vision,Inscribed figure,Object model,Artificial intelligence,Cuboid,Adaptive learning,Mathematics | Conference |
Volume | Issue | ISSN |
2016 | 1 | 1050-4729 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Pieropan | 1 | 53 | 4.39 |
| Niklas Bergström | 2 | 69 | 6.00 |
| Masatoshi Ishikawa | 3 | 903 | 163.13 |
| Danica Kragic | 4 | 2070 | 142.17 |
| hedvig kjellstrom | 5 | 491 | 42.24 |