An HMM Model with a Recurrent Kernel in High Dimensional Space Applied to Vehicle Trajectory Recognition

In this paper, a new type of the HMM model is presented with a recurrent kernel in the high dimensional space, HDS. HMM in the HDS have three properties: HDS is a linear space relative to the input space, creation of an interaction between HMM models, and it is a kind of hierarchical classification. Also, recurrent kernel in HMM model has a few advantages as, reducing of noise in noisy data and parameter smoothing in HMM. This approach was applied to synthetic motion and vehicle trajectory recognition; Experimental results show an increase of 32.1% for synthetic motion recognition and 9.7% for vehicle trajectory recognition performance in comparison to conventional HMM

Keywords:

HMM , High Dimensional Space , Recurrent Kernel , Motion Recognition , Multi object Tracking