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HDP-HMM-SCFG: A Novel Model for Trajectory Representation and Classification
2011
Procedia Engineering
In this paper, we propose a novel model, HDP-HMM-SCFG, for representing and classifying trajectories. Trajectories are represented by stochastic grammar, where trajectory segments are considered as observations emitted by the grammar terminals, which are attached with HMMs. In order to learn the parameters of SCFG, we employ hierarchical Dirichlet Processes (HDP) as the nonparameter prior of the distribution of the parameters, and obtain the model of HDP-HMM-SCFG. Then, we propose a 3-level CRP
doi:10.1016/j.proeng.2011.08.117
fatcat:e3welr5lurebpainfdkwjrv7di