Learning to recognise 3D human action from a new skeleton‐based representation using deep convolutional neural networks
Recognising human actions in untrimmed videos is an important challenging task. An effective three‐dimensional (3D) motion representation and a powerful learning model are two key factors influencing recognition performance. In this study, the authors introduce a new skeleton‐based representation fo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2018.5014 |