MOANA: An Online Learned Adaptive Appearance Model for Robust Multiple Object Tracking in 3D
Multiple object tracking has been a challenging field, mainly due to noisy detection sets an identity switch caused by occlusion and similar appearance among nearby targets. Previous works rely on appearance models that are built on an individual or several selected frames for the comparison of feat...
Main Authors: | Zheng Tang, Jenq-Neng Hwang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8660675/ |
Similar Items
-
Appearance Guidance Attention for Multi-Object Tracking
by: Yong Chen, et al.
Published: (2021-01-01) -
PAE: Portable Appearance Extension for Multiple Object Detection and Tracking in Traffic Scenes
by: Ibrahim Soliman Mohamed, et al.
Published: (2022-01-01) -
Multiple Object Tracking With Attention to Appearance, Structure, Motion and Size
by: Hasith Karunasekera, et al.
Published: (2019-01-01) -
Robust object tracking via online discriminative appearance modeling
by: Wei Liu, et al.
Published: (2019-10-01) -
Multiple Object Tracking With Appearance Feature Prediction and Similarity Fusion
by: Zhiyuan Li, et al.
Published: (2023-01-01)