Name
Abstract | ||
|---|---|---|
This paper presents a robust object tracking method using a sparse shape-based object model. Our approach consists of three ingredients namely shapes, a motion model and a sparse (non-binary) subsampling of colours in background and foreground parts based on the shape assumption. The tracking itself is inspired by the idea of having a short-term and a long-term memory. A lost object is "missed" by the long-term memory when it is no longer recognized by the short-term memory. Moreover, the long-term memory allows to re-detect vanished objects and using their new position as a new initial position for object tracking. The short-term memory is implemented with a new Monte Carlo variant which provides a heuristic to cope with the loss-of-diversity problem. It enables simultaneous tracking of multiple (visually) identical objects. The long-term memory is implemented with a Bayesian Multiple Hypothesis filter. We demonstrate the robustness of our approach with respect to object occlusions and non-Gaussian/non-linear movements of the tracked object. We also show that tracking can be significantly improved by using compensating ego-motion. Our approach is very scalable since one can tune the parameters for a trade-off between precision and computational time. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-74024-7_15 | RoboCup 2009 |
Keywords | Field | DocType |
towards probabilistic shape vision,tracked object,object tracking,long-term memory,short-term memory,practical approach,new monte carlo variant,sparse shape-based object model,identical object,simultaneous tracking,lost object,robust object tracking method,long term memory,short term memory,monte carlo,object model | Computer vision,Monte Carlo method,Heuristic,Computer science,Simulation,Particle filter,Object model,Robustness (computer science),Video tracking,Artificial intelligence,Probabilistic logic,Scalability | Conference |
Volume | ISSN | Citations |
4434 | 0302-9743 | 3 |
PageRank | References | Authors |
0.44 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sven Olufs | 1 | 21 | 4.67 |
| Florian Adolf | 2 | 3 | 0.44 |
| Ronny Hartanto | 3 | 54 | 6.12 |
| Paul-gerhard Plöger | 4 | 78 | 13.82 |