An Adaptive PHD Filter for Multitarget Tracking with Multispectral Data Fusion
In order to improve the detection and tracking performance of multiple targets from IR multispectral image sequences, the approach based on spectral fusion algorithm and adaptive probability hypothesis density (PHD) filter is proposed. Firstly, the nonstationary adaptive suppression method is propos...
Saved in:
Main Authors: | Guoliang Zhang, Chunling Yang, Yan Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2015-01-01
|
Series: | Journal of Spectroscopy |
Online Access: | http://dx.doi.org/10.1155/2015/179039 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiple-Model Cardinality Balanced Multitarget Multi-Bernoulli Filter for Tracking Maneuvering Targets
by: Xianghui Yuan, et al.
Published: (2013-01-01) -
Machine Learning-Based Multitarget Tracking of Motion in Sports Video
by: Xueliang Zhang, et al.
Published: (2021-01-01) -
Improved YOLOX-DeepSORT for Multitarget Detection and Tracking of Automated Port RTG
by: ZHENGTAO YU, et al.
Published: (2024-01-01) -
Multitarget Pedestrian Tracking Algorithm Based on a Contour Template with Multiscale Stability
by: Hui Liu, et al.
Published: (2022-01-01) -
Retracted: Deep Learning-Based Multitarget Motion Shadow Rejection and Accurate Tracking for Sports Video
by: null Complexity
Published: (2023-01-01)