Name
Abstract | ||
|---|---|---|
In this paper we propose a cascaded hierarchical framework for object detection and tracking. We claim that, by integrating both detection and tracking into a unified framework, the detection and tracking of multiple moving objects in a complicated environment become more robust. Under the proposed architecture, detection and tracking cooperate with each other. Based on the result of moving object detection, a dynamic model is adaptively maintained for object tracking. On the other hand, the updated dynamic model is used for both temporal prior propagation of object labels and the update of foreground/background models, which step further to help the detection of moving objects. The experiments show accurate results can be obtained under situations with foreground/background appearance ambiguity, camera shaking, and object occlusion. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5649539 | ICIP |
Keywords | Field | DocType |
object labeling,dynamic tracking system,background subtraction,object occlusion,dynamic model,object tracking,foreground-background appearance ambiguity,object detection,moving object detection,cascaded hierarchical framework,hierarchical framework,camera shaking,image motion analysis,foreground background,tracking system,labeling,tracking,pixel,predictive models | Background subtraction,Computer vision,Object detection,Viola–Jones object detection framework,Object-class detection,Pattern recognition,Computer science,Tracking system,Video tracking,Pixel,Artificial intelligence,Ambiguity | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 1 |
PageRank | References | Authors |
0.35 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ching-chun Huang | 1 | 135 | 9.63 |
| Sheng-Jyh Wang | 2 | 202 | 23.46 |