  In many cases, such as trajectories clustering and classification, we often
divide a trajectory into segments as preprocessing. In this paper, we propose a
trajectory semantic segmentation method based on learned behavior models. In
the proposed method, we learn some behavior models from video sequences. Next,
using learned behavior models and a hidden Markov model, we segment a
trajectory into semantic segments. Comparing with the Ramer-Douglas-Peucker
algorithm, we show the effectiveness of the proposed method.
