Robust multi‐feature visual tracking via multi‐task kernel‐based sparse learning-Reference-Cited by-同舟云学术

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Robust multi‐feature visual tracking via multi‐task kernel‐based sparse learning

Published:2017-10-30 Issue:12 Volume:11 Page:1172-1178
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Kang Bin¹,Zhu Wei‐Ping²,Liang Dong³

Affiliation:

1. College of Internet of Things, Nanjing University of Posts and TelecommunicationsNanjing210003People's Republic of China

2. Department of Electrical and Computer EngineeringConcordia UniversityMontrealnQuebecCanadaH3G 1M8

3. College of Computer Science and Technology, Nanjing University of Aeronautics and AstronauticsNanjing211106People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2016.1062

Reference46 articles.

1. Particle filter to track multiple people for visual surveillance

2. 2005 IEEE Conf. Computer Vision and Pattern Recognition Z. Zhu Q. Ji Eye gaze tracking under natural head movements

3. Particle filters for positioning, navigation, and tracking

4. Visual tracking with online Multiple Instance Learning

5. Fast Compressive Tracking

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