Real-Time Tracking with Multi-center Kernel Correlation Filter

Recently, visual object tracking based on kernel correlation filtering has achieved great success. Application of robust feature, such as the Histogram of Oriented Gradients, is an important reason for the success of the kernel correlation filtering. However, the extraction of the HOG feature may bias the estimation of the target. To overcoming such kind of deviation, this paper proposes a real-time tracker with a multi-center strategy based on the kernel correlation filtering. Finally, abundant experimental results show that the multi-center kernel correlation filtering tracker of this paper has been made great progress relative the kernel correlation filtering tracker.

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