Multi-Object Tracking with Predictive Information Fusion and Adaptive Measurement Noise
Multi-object tracking (MOT) aims to detect objects in video sequences and associate them across frames. Currently, the mainstream research direction regarding MOT is the tracking-by-detection (TBD) framework. Tracking results are highly sensitive to detection outputs, and challenges from object occl...
Saved in:
Main Authors: | Xiaohui Cheng, Haoyi Zhao, Yun Deng, Shuangqin Shen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/2/736 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage
by: Imad Eddine Toubal, et al.
Published: (2024-01-01) -
View adaptive multi-object tracking method based on depth relationship cues
by: Haoran Sun, et al.
Published: (2025-01-01) -
Online Boosting tracking algorithm combined with occlusion sensing
by: Ya-wen WANG, et al.
Published: (2016-09-01) -
Object detection and tracking in video sequences: formalization, metrics and results
by: R. P. Bohush, et al.
Published: (2021-03-01) -
A scale adaptive visual object tracking algorithm based on weighted neutrosophic similarity coefficient
by: Keli HU, et al.
Published: (2018-05-01)