Trajectory-based vehicle tracking at low frame rates

Giyoung Lee, Rammohan Mallipeddi, Minho Lee

Abstract: Highlights•A new vehicle tracking method is proposed for an embedded traffic surveillance system.•The proposed method demonstrates efficient tracking performance at a low frame rate.•The proposed method employs greedy data association based on appearance and position similarities.•To manage abrupt appearance changes, manifold learning is used.•To manage abrupt motion changes, trajectory information is used to predict the next probable position.