Name
Abstract | ||
|---|---|---|
In a complex environment, simultaneous object recognition and tracking has been one of the challenging topics in computer vision and robotics. Current approaches are usually fragile due to spurious feature matching and local convergence for pose determination. Once a failure happens, these approaches lack a mechanism to recover automatically. In this paper, data-driven unfalsified control is propo... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCYB.2015.2495157 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Visual servoing,Feature extraction,Adaptation models,Visualization,Target tracking,Cameras | Computer vision,Feature (computer vision),Tracking system,Feature extraction,Robustness (computer science),Video tracking,Eye tracking,Visual servoing,Artificial intelligence,Mathematics,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
46 | 12 | 2168-2267 |
Citations | PageRank | References |
1 | 0.35 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ping jiang | 1 | 2 | 1.09 |
| Yongqiang Cheng | 2 | 133 | 29.99 |
| Xiaonian Wang | 3 | 8 | 3.20 |
| Zuren Feng | 4 | 423 | 35.28 |