IOF-Tracker: A Two-Stage Multiple Targets Tracking Method Using Spatial-Temporal Fusion Algorithm
Multi-object tracking aims to track multiple objects across consecutive frames in a video, assigning a unique classifier to each object. However, issues such as occlusions, directional changes, or shape alterations can cause appearance variations, leading to detection and matching problems that in t...
Saved in:
Main Authors: | Hongbin Liu, Yongze Zhao, Peng Dong, Xiuyi Guo, Yilin Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/1/107 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spatial-temporal initialization dilemma: towards realistic visual tracking
by: Chang Liu, et al.
Published: (2024-12-01) -
Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting
by: Ang Guo, et al.
Published: (2025-01-01) -
Spatio-Temporal Feature Aware Vision Transformers for Real-Time Unmanned Aerial Vehicle Tracking
by: Hao Zhang, et al.
Published: (2025-01-01) -
LATrack: Limited Attention for Visual Object Tracking
by: Jian Shi, et al.
Published: (2025-01-01) -
Multi-Object Tracking with Predictive Information Fusion and Adaptive Measurement Noise
by: Xiaohui Cheng, et al.
Published: (2025-01-01)