Learning hierarchical spatio-temporal pattern for human activity prediction.

•A novel approach to learning a hierarchical spatio-temporal pattern of human actions.•Spatio-temporal pattern can be learned by a Hierarchical Self-Organizing Map (HSOM).•The associative weights between HSOM can be obtained through Hebbian learning.•Ongoing activities can be predicted by Variable order Markov Model (VMM).