Name
Title | ||
|---|---|---|
View Transformation Model Incorporating Quality Measures for Cross-View Gait Recognition. |
Abstract | ||
|---|---|---|
Cross-view gait recognition authenticates a person using a pair of gait image sequences with different observation views. View difference causes degradation of gait recognition accuracy, and so several solutions have been proposed to suppress this degradation. One useful solution is to apply a view transformation model (VTM) that encodes a joint subspace of multiview gait features trained with aux... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TCYB.2015.2452577 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Accuracy,Gait recognition,Training,Probes,Feature extraction,Measurement uncertainty,Image sequences | Population,ENCODE,Normalization (statistics),Subspace topology,Gait,Pattern recognition,Measurement uncertainty,Posterior probability,Feature extraction,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
46 | 7 | 2168-2267 |
Citations | PageRank | References |
30 | 0.82 | 50 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daigo Muramatsu | 1 | 262 | 24.88 |
| Yasushi Makihara | 2 | 1012 | 70.67 |
| Yasushi Yagi | 3 | 1752 | 186.22 |