HIGHLIGHTS
SUMMARY
The authors propose a novel fusion scheme that combines response maps from different feature spaces to take advantages of the fact that convolutional features are complementary to handcrafted features normally associated with physical properties. Although the search range of BACF is enlarged, this also leads to that the resolution of the target area in the feature space becomes smaller than that of the DCF-based trackers. Unfortunately, the similar scheme that combines convolutional features with the BACF leads to a decrease in tracking performance due to the resolution reduction of the feature map corresponding . . .
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