Name
Abstract | ||
|---|---|---|
In order to improve the precision of tracking in real-time, the bandwidth of tracking should be changed according to the change of object’s scale. Based on mean shift algorithm and the target center in every frame located by probability method, this thesis puts forward a self-adaptive algorithm for updating views. Then by combining the normalized moment of inertia (NMI) feature, the center of tracking object is located in real-time. The experiments show that this method can choose the proper size of tracking bandwidth when the object size changing and have strong anti-jamming. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FSKD.2009.468 | FSKD (5) |
Keywords | Field | DocType |
object tracking,moment of inertia,mean shift,real time | Normalization (statistics),Computer science,Artificial intelligence,Kernel (linear algebra),Computer vision,Object detection,Algorithm design,Pattern recognition,Algorithm,Video tracking,Bandwidth (signal processing),Pixel,Mean-shift,Machine learning | Conference |
Volume | Issue | Citations |
5 | null | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aibin Chen | 1 | 4 | 5.88 |
| Zixing Cai | 2 | 1525 | 66.96 |
| Deyi Dong | 3 | 0 | 0.34 |