Piecewise mean-reverting stochastic processes have been recently proposed and validated as an effective model for long-term object prediction. In this paper, we exploit the Ornstein-Uhlenbeck (OU) dynamic model to represent ...

In this work, we propose a data driven trajectory forecasting algorithm that utilizes both recorded historical and streaming trajectory observations. The algorithm performs Bayesian inference on a directed graph the walks ...