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Content Provider | IET Digital Library |
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Author | Liu, Qi Zhao, Xiaoguang Hou, Zengguang |
Abstract | Visual tracking is a popular and challenging topic in computer vision and robotics. Owing to changes in the appearance of the target and complicated variations that may occur in various scenes, online learning scheme is necessary for advanced visual tracking framework to adopt. This paper briefly introduces the challenges and applications of visual tracking and focuses on discussing the state-of-the-art online-learning-based tracking methods by category. We provide detail descriptions of representative methods in each category, and examine their pros and cons. Moreover, several most representative algorithms are implemented to provide quantitative reference. At last, we outline several trends for future visual tracking research. |
Starting Page | 419 |
Ending Page | 428 |
Page Count | 10 |
ISSN | 17519632 |
Volume Number | 8 |
e-ISSN | 17519640 |
Issue Number | Issue 5, Oct (2014) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cvi/8/5 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2013.0134 |
Journal | IET Computer Vision |
Publisher Date | 2014-01-29 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Advanced Visual Tracking Framework Computer Vision Computer Vision And Image Processing Technique Knowledge Engineering Technique Learning in AI Object Tracking Online Learning Scheme Online-learning-based Tracking Method Optical, Image And Video Signal Processing Robot Vision Robotics Single-target Visual Tracking Method Target Appearance |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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