Learning spatial–temporal features via a pose-flow relational model for action recognition
Pose-based action recognition has always been an important research field in computer vision. However, most existing pose-based methods are built upon human skeleton data, which cannot be used to exploit the feature of the motion-related object, i.e., a crucial clue of discriminating human actions....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2020-07-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0011161 |