Learning Clip Representations for Skeleton-Based 3D Action Recognition
This paper presents a new representation of skeleton sequences for 3D action recognition. Existing methods based on hand-crafted features or recurrent neural networks cannot adequately capture the complex spatial structures and the long-term temporal dynamics of the skeleton sequences, which are ver...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 27(2018), 6 vom: 30. Juni, Seite 2842-2855
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| 1. Verfasser: |
Ke, Qiuhong
(VerfasserIn) |
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| Weitere Verfasser: |
Bennamoun, Mohammed,
An, Senjian,
Sohel, Ferdous,
Boussaid, Farid |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2018
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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