Name
Abstract | ||
|---|---|---|
The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICMLC.2013.6890893 | ICMLC |
Keywords | DocType | Volume |
video signal processing,video knowledge base,knowledge based systems,complex event recognition,arbitrary complex spatio-temporal event,Video pattern recognition,hierarchical knowledge-based framework,image recognition,Hierarchical approach,complex high-level event automatic detection,uncertainty reasoning procedures,uncertainty handling,Uncertainty reasoning,low level event descriptions,Complex event recognition,video event knowledge,Knowledge base | Conference | 04 |
ISSN | Citations | PageRank |
2160-133X | 1 | 0.36 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xueqin Liu | 1 | 1 | 0.36 |
| Kathy M. Clawson | 2 | 9 | 1.83 |
| hui wang | 3 | 76 | 17.01 |
| Bryan W. Scotney | 4 | 670 | 82.50 |
| Jun Liu | 5 | 644 | 56.21 |