A robust local sparse tracker with global consistency constraint

Xinhua You, Xin Li, Zhenyu He, Xiaofeng Zhang

Abstract: Highlights•The first contribution is proposing a novel local sparse model with global constraint, which can reduce the drifting problems.•The second contribution is giving a two-stage algorithm to exploit the partial and spatial information without overfitting problems.•The third contribution is raising exploiting occlusion information to guide the template update, which can improve the template update strategy.