We propose novel multi-fused features for online HAR system.
They are skeleton joint features including joint features DT, DK, M, ⊖ and shape feature HOG-DDS.
The HAR systems recognize human activities from continuous sequences of depth map.
It trains the hidden Markov model (HMM) with the code vectors of the multi-fused features.
It outperforms the state-of-the-art HAR methods in terms of recognition accuracy.