Name
Abstract | ||
|---|---|---|
Multi-object tracking in monocular video sequence is a challenging work when objects are occluded and objects' number is unknown or varies during tracking. In this paper, a multi-object parallel tracking method is proposed based on Bayesian framework. First, our method is designed to avoid huge amount of computation as required in multi-object joint tracking method. Second, our method can explicitly reason about occlusions, the depth ordering of interactive objects is inferred. We calculate the observation transition matrix to determine the movement transition between successive frames, given the object observations obtained in each frame. Each tracker could also collaborate with one another to decide which object is occluding and which is occluded when occlusion occurs. Our experiment results demonstrate that our method of using multiple trackers could automatically initialize and track multiple objects with varying numbers and occlusion. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSO.2009.378 | CSO (2) |
Keywords | Field | DocType |
multiple tracker,video signal processing,multi-object joint tracking method,object observation,bayesian framework,bayes methods,computer graphics,multi-object tracking,explicit reasoning,multiple object,tracking,interactive object,movement transition,object detection,monocular video sequence,observation transition matrix,multi-object parallel tracking method,occlusion,video surveillance,sampling methods,collaboration,estimation,robustness,object tracking,design methodology,bayesian methods,particle filters,transition matrix,distributed computing,data mining | Computer vision,Object detection,BitTorrent tracker,Occlusion,Computer science,Particle filter,Video tracking,Artificial intelligence,Computer graphics,Computation,Bayesian probability | Conference |
Volume | ISBN | Citations |
2 | 978-0-7695-3605-7 | 0 |
PageRank | References | Authors |
0.34 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingling Wang | 1 | 7 | 4.24 |
| Yan Ma | 2 | 0 | 0.68 |
| Chuanzhen Li | 3 | 7 | 3.57 |
| Hui Wang | 4 | 177 | 43.68 |
| Jianbo Liu | 5 | 7 | 2.91 |