Name
Abstract | ||
|---|---|---|
In this paper, we propose an event-guided support vector machine (ESVM) for tracking high-speed moving objects. Tracking fast-moving objects with low frame rate cameras is always difficult due to motion blur and large displacements. The accuracy problem can be solved by using high frame rate cameras at the expense of tremendous computational cost. For this issue, our ESVM incorporates event-based ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSVT.2018.2841516 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | Field | DocType |
Tracking,Robot sensing systems,Support vector machines,Cameras,Computational efficiency,Lighting,Search problems | Structured support vector machine,Computer vision,BitTorrent tracker,Pattern recognition,Computer science,Support vector machine,Motion blur,Pixel,Artificial intelligence,Frame rate,Timestamp,Trajectory | Journal |
Volume | Issue | ISSN |
28 | 9 | 1051-8215 |
Citations | PageRank | References |
2 | 0.36 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Huang | 1 | 5 | 2.11 |
| Shi-Zheng Wang | 2 | 77 | 8.39 |
| Menghan Guo | 3 | 8 | 3.52 |
| Shoushun Chen | 4 | 177 | 26.85 |