Evaluation of a skeleton-based method for human activity recognition on a large-scale RGB-D dataset

By Enea Cippitelli, Ennio Gambi, Susanna Spinsante, Francisco Flórez-Revuelta. 2016

22 citations recorded by the source corpus.

Paper accepted for presentation at 2nd IET International Conference on Technologies for Active and Assisted Living (TechAAL), 24-25 October 2016, IET London: Savoy Place.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition

Citations in the corpus

• Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates (2017, neutral): “[77] Geometric 48.”