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...
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Détails bibliographiques
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 27(2018), 6 vom: 08. Juni, Seite 2842-2855
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| Auteur principal: |
Ke, Qiuhong
(Auteur) |
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| Autres auteurs: |
Bennamoun, Mohammed,
An, Senjian,
Sohel, Ferdous,
Boussaid, Farid |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2018
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Sujets: | Journal Article |
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