Name
Abstract | ||
|---|---|---|
This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandonand Steal bagevent. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72590-9_57 | International Conference on Computational Science (4) |
Keywords | Field | DocType |
real time,background subtraction,bayesian network,object tracking | Background subtraction,Computer vision,Segmentation,Computer science,ALARM,Inference,Real-time computing,Video tracking,Bayesian network,Artificial intelligence,Mobile phone,Event recognition | Conference |
Volume | ISSN | Citations |
4490 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sooyeong Kwak | 1 | 39 | 5.65 |
| Guntae Bae | 2 | 2 | 1.40 |
| Kilcheon Kim | 3 | 23 | 2.81 |
| Hyeran Byun | 4 | 505 | 65.97 |