Kernel correlation filters for visual tracking with adaptive fusion of heterogeneous cues-Reference-Cited by-同舟云学术

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Kernel correlation filters for visual tracking with adaptive fusion of heterogeneous cues

Published:2018-04 Issue: Volume:286 Page:109-120
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Bai Bing,Zhong Bineng,Ouyang Gu,Wang Pengfei,Liu Xin,Chen Ziyi,Wang Cheng

Funder

Natural Science Foundation of China

Natural Science Foundation of Fujian Province

2015 Program

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference34 articles.

1. Visual object tracking using adaptive correlation filters;Bolme,2010

2. Beyond hard negative mining: efficient detector learning via block-circulant decomposition;Henriques,2013

3. High-speed tracking with kernelized correlation filters;Henriques;IEEE Trans. Pattern Anal. Mach. Intell.,2015

4. A scale adaptive kernel correlation filter tracker with feature integration;Li,2014

5. Robust visual tracking via multi-task sparse learning;Zhang,2012

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4. A novel kernelized correlation filter by fusing multiple feature response maps, enhanced target re-detection, and improved model updating for visual tracking;The Visual Computer;2021-07-31

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