Fast Fourier Transform Networks for Object Tracking Based on Correlation Filter

Fast Fourier Transform Networks for Object Tracking Based on Correlation Filter

In this paper, we propose fast Fourier transform networks for object tracking, called FFTNet. FFTNet is a correlation filter (CF)-based tracker that integrates two main components of CF, i.e., auto correlation and cross correlation between the features of two images. Thus, FFTNet takes full advantag...

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Bibliographic Details
Main Authors: Zhangping He, Zhendong Zhang, Cheolkon Jung
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Object tracking
auto correlation
cross correlation
convolutional neural networks
correlation filter
fast Fourier transform
Online Access:https://ieeexplore.ieee.org/document/8249803/

Internet

https://ieeexplore.ieee.org/document/8249803/

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