Learning hierarchical spatio-temporal pattern for human activity prediction.
Journal of Visual Communication and Image Representation(2016)
摘要
•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).
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关键词
Skeleton joints,3D action feature representation,Self-organizing map,Hebbian learning,Variable order Markov model,Probabilistic suffix tree,RGB-D dataset,3D trajectory segmentation
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