Multi-Target Video Tracking Based on Improved Data Association and Mixed Kalman/<inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math> </inline-formula> Filtering-Reference-Cited by-同舟云学术

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Multi-Target Video Tracking Based on Improved Data Association and Mixed Kalman/ $H_{\infty }$ Filtering

Published:2016-11 Issue:21 Volume:16 Page:7693-7704
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Howard,Nguang Sing Kiong^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/7579242/07555348.pdf?arnumber=7555348

Cited by 21 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. New joint probabilistic data association algorithm based on variational Bayesian adaptive moment estimation;Transactions of the Institute of Measurement and Control;2023-08-22

2. An innovative method for scene recognition and target tracking for adaptive cruise control in complex traffic environment;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2023-03-03

3. Multiple targets video tracking based on extended kalman filter in combination with particle swarm optimization for intelligent applications;SN Applied Sciences;2023-02-16

4. Multi-object tracking based on network flow model and ORB feature;Applied Intelligence;2022-02-03

5. A New Method for Surface-to-Air Video Detection and Tracking of Airborne Vehicles;International Journal of Pattern Recognition and Artificial Intelligence;2022-01-17

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