Statistical Degradation Analysis for Real-Time Tracking in Severely Degraded Videos

Recently, Correlation Filter have been widely applied in object tracking, by combining different features, correlation filter based methods can robustly track the target in various situations like illumination change, target deformation, motion blur and camera defocus. However, those methods can hardly deal with non-uniform degradations. In this paper, we proposed a Statistical Degradation Model to handle those issues, in our model, we apply colour-based statistical feature for deformation and defocus, gradient distributions for illumination change and colour degradation, degradation distribution for fast motion and motion blur. By combining those features our method could achieve obvious improvement in severely degraded videos, and outperform some state-of-the-art methods in popular benchmark OTB2013.

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