ML Anthology

Action Recognition from RGB-D Data: Comparison and Fusion of Spatio-Temporal Handcrafted Features and Deep Strategies

Maryam Asadi-Aghbolaghi, Hugo Bertiche, Vicent Roig, Shohreh Kasaei, Sergio Escalera
ICCVW 2017 pp. 3179-3188
doi:10.1109/ICCVW.2017.376 /iccvw/2017/asadiaghbolaghi2017iccvw-action/
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Cite

Text

Asadi-Aghbolaghi et al. "Action Recognition from RGB-D Data: Comparison and Fusion of Spatio-Temporal Handcrafted Features and Deep Strategies." IEEE/CVF International Conference on Computer Vision Workshops, 2017. doi:10.1109/ICCVW.2017.376

Markdown

[Asadi-Aghbolaghi et al. "Action Recognition from RGB-D Data: Comparison and Fusion of Spatio-Temporal Handcrafted Features and Deep Strategies." IEEE/CVF International Conference on Computer Vision Workshops, 2017.](https://mlanthology.org/iccvw/2017/asadiaghbolaghi2017iccvw-action/) doi:10.1109/ICCVW.2017.376

BibTeX

@inproceedings{asadiaghbolaghi2017iccvw-action,
  title     = {{Action Recognition from RGB-D Data: Comparison and Fusion of Spatio-Temporal Handcrafted Features and Deep Strategies}},
  author    = {Asadi-Aghbolaghi, Maryam and Bertiche, Hugo and Roig, Vicent and Kasaei, Shohreh and Escalera, Sergio},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2017},
  pages     = {3179-3188},
  doi       = {10.1109/ICCVW.2017.376},
  url       = {https://mlanthology.org/iccvw/2017/asadiaghbolaghi2017iccvw-action/}
}