An Anti-Drift Background-Aware Correlation Filter for Visual Tracking in Complex Scenes

An Anti-Drift Background-Aware Correlation Filter for Visual Tracking in Complex Scenes

The model drift problem is an inevitable problem for online visual tracking. Model drift can amplify the false tracking result over time and lead to failed tracking finally. Background-aware correlation filter (BACF) tracker obtains the training samples from negative background patches instead of sh...

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Bibliographic Details
Main Authors: Shanshan Luo, Baoqing Li, Xiaobing Yuan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Visual tracking
correlation filter
background-aware
temporal consistency
channel selection
model drift
Online Access:https://ieeexplore.ieee.org/document/8932485/

Internet

https://ieeexplore.ieee.org/document/8932485/

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