Robust Visual Tracking via Multilayer CaffeNet Features and Improved Correlation Filtering

Robust Visual Tracking via Multilayer CaffeNet Features and Improved Correlation Filtering

For problems related to the robust tracking of visual objects in various challenging tracking conditions, a robust visual tracking method based on multilayer convolutional features and correlation filtering is proposed. To solve the problems of mean deviation and insufficient discrimination ability...

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Bibliographic Details
Main Authors: Yuqi Xiao, Difu Pan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Convolutional neutral network
correlation filter
target tracking
computer vision technology
Online Access:https://ieeexplore.ieee.org/document/8922754/

Internet

https://ieeexplore.ieee.org/document/8922754/

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