Survey of single‐target visual tracking methods based on online learning-Reference-Cited by-同舟云学术

Survey of single‐target visual tracking methods based on online learning

Published:2014-10 Issue:5 Volume:8 Page:419-428
ISSN:1751-9640
Container-title:IET Computer Vision
language:en
Short-container-title:IET Computer Vision

Author:

Liu Qi¹,Zhao Xiaoguang¹,Hou Zengguang¹

Affiliation:

1. The State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation, Chinese Academy of SciencesBeijing100080People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cvi.2013.0134

Reference78 articles.

1. Robust online appearance models for visual tracking

2. Visual Tracking and Recognition Using Appearance-Adaptive Models in Particle Filters

3. Online Updating Appearance Generative Mixture Model for Meanshift Tracking

4. A level set framework using a new incremental, robust Active Shape Model for object segmentation and tracking

5. An Incremental PCA-HOG Descriptor for Robust Visual Hand Tracking

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generative online learning of appearance modeling approaches for visual tracking;Journal of Optics;2023-11-09

2. Discriminative learning of online appearance modeling methods for visual tracking;Journal of Optics;2023-07-22

3. Improved anti-occlusion object tracking algorithm using Unscented Rauch-Tung-Striebel smoother and kernel correlation filter;Journal of King Saud University - Computer and Information Sciences;2022-09

4. Multi-Type Object Tracking Based on Residual Neural Network Model;Symmetry;2022-08-15

5. Object tracking algorithm by moving video camera;Doklady of the National Academy of Sciences of Belarus;2020-05-17