Object tracking under nonuniform illumination with adaptive correlation filtering

A real-time system for illumination-invariant object tracking is proposed. The system is able to estimate at high-rate the position of a moving target in an input scene when is corrupted by the presence of a high cluttering background and nonuniform illumination. The position of the target is estimated with the help of a filter bank of space-variant correlation filters. The filters in the bank, adapt their parameters according to the local statistical parameters of the observed scene in a small region centered at coordinates of a predicted position for the target in each frame. The prediction is carried out by exploiting information of present and past frames, and by using a dynamic motion model of the target in a two-dimensional plane. Computer simulation results obtained with the proposed system are presented and discussed in terms of tracking accuracy, computational complexity, and tolerance to nonuniform illumination.