A compound Sugeno type system with weighted average memory for object tracking

Object tracking is a paramount task in video surveillance systems. Although many efforts have been accomplished on object tracking during the last years more work is still needed in order to generate more robust systems. A new fuzzy method for object tracking is presented in this paper. The proposed method is composed of two Sugeno type systems with weighted average memory output functions. One of the systems deals with the horizontal displacement and the other with the vertical. The proposed method is tested on different video sequences commonly encountered in video surveillance scenes. The RMSE metric is used to measure the performance of the proposed method. Findings indicate the method can track the object of interest very closely to its real position in most of the frames in different scenarios.