A new algorithm for target recognition and tracking for robot vision system

Target recognition and tracking is the key destination in robot vision system. A new efficient algorithm is introduced in this paper to overcome the contradiction among the complexity of algorithm, tracking precision, and the rapidity in real-time system. Firstly, the algorithm is based on the feature of template cursory matching by lowering resolution and using sequential similarity detection algorithm (SSDA) with four items of improvement to locate the position. Secondly, it brings forward a template update algorithm based on confidence level Maximum Close Distance, as the target varying posture and moving constantly. Finally, Kalman filter algorithm is used to estimate the position and it can reduce the ratio of losing target when the target is sheltered. The experiments and simulations show that the algorithms given in the paper have advantages of improving orientation precision, rapidity, practicability, and robustness in orientating target.