Name
Abstract | ||
|---|---|---|
Cross-view person identification (CVPI) from multiple temporally synchronized videos taken by multiple wearable cameras from different, varying views is a very challenging but important problem, which has attracted more interest recently. Current state-of-the-art performance of CVPI is achieved by matching appearance and motion features across videos, while the matching of pose features does not w... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIP.2019.2899782 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Three-dimensional displays,Videos,Cameras,Two dimensional displays,Synchronization,Pose estimation | Computer vision,Synchronization,Pattern recognition,Wearable computer,3D pose estimation,Pose,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
28 | 8 | 1057-7149 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoqiang Liang | 1 | 15 | 5.04 |
| X. Lan | 2 | 165 | 30.34 |
| Xingyu Chen | 3 | 154 | 33.13 |
| Kang Zheng | 4 | 42 | 7.41 |
| Song Wang | 5 | 954 | 79.55 |
| Nanning Zheng | 6 | 3975 | 329.18 |