Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Equivalence of Correlation Filter and Convolution Filter in Visual
  Tracking   (Discriminative) Correlation Filter has been successfully applied to visual
tracking and has advanced the field significantly in recent years. Correlation
filter-based trackers consider visual tracking as a problem of matching the
feature template of the object and candidate regions in the detection sample,
in which correlation filter provides the means to calculate the similarities.
In contrast, convolution filter is usually used for blurring, sharpening,
embossing, edge detection, etc in image processing. On the surface, correlation
filter and convolution filter are usually used for different purposes. In this
paper, however, we proves, for the first time, that correlation filter and
convolution filter are equivalent in the sense that their minimum mean-square
errors (MMSEs) in visual tracking are equal, under the condition that the
optimal solutions exist and the ideal filter response is Gaussian and
centrosymmetric. This result gives researchers the freedom to choose
correlation or convolution in formulating their trackers. It also suggests that
the explanation of the ideal response in terms of similarities is not
essential.

16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
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The categories of this paper are: adap-org
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: hep-lat
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The categories of this paper are: solv-int
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The categories of this paper are: quant-ph