Table 4.

Average recognition accuracies (%) of our approach and comparison with previous works using the CAD-60 dataset. The best accuracy level is presented in bold.

Methods	Year	Acc. (%)
Dynamic Bayesian Mixture Model [23]	2014	91.9%
Support Vector Machine + Hidden Markov Model [26]	2015	77.3%
Multiclass Support Vector Machine [25]	2016	93.5
Classifier Ensemble [12]	2018	92.3%
Weighted 3D joints [41]	2019	94.4%
Our System	2020	95.5%