Name
Abstract | ||
|---|---|---|
The detection of moving objects is a key step in the traffic video monitoring system. The most common way to detect moving objects is background subtraction and the critical technique is the background modeling. In this paper, we propose a method combining LBP with Gauss for the detection of the moving objects. We adopt the method of parallel processing in order to improve the processing speed in the implementation of the algorithm. And the video sequences are used to test the proposed method. Experiments show that our methods have high real-time in background updating. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICMLC.2012.6359563 | ICMLC |
Keywords | Field | DocType |
parallel processing,traffic video monitoring system,dual background modeling,video sequences,monitoring,traffic engineering computing,gaussian tracking,lbp,traffic image,image sequences,object detection,moving object detection,background subtraction,background modeling,gaussian,detection of moving objects | Background subtraction,Object detection,Computer vision,Gauss,Monitoring system,Pattern recognition,Computer science,Parallel processing,Image based,Gaussian,Artificial intelligence | Conference |
Volume | ISSN | ISBN |
4 | 2160-133X | 978-1-4673-1484-8 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juntao Xue | 1 | 3 | 1.79 |
| Cuirong Wang | 2 | 110 | 15.54 |
| Shao-Fang Xing | 3 | 1 | 0.72 |