Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)

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Unmanned Aerial Vehicle Target Tracking Systems in Complex Environments Based on Visual Enhancement Technology

Authors
Tianlin Guo1, *
1School of International Education, Beijing University of Chemical Technology, Beijing, 102200, China
*Corresponding author. Email: 2024090082@buct.edu.cn
Corresponding Author
Tianlin Guo
Available Online 24 April 2026.
DOI
10.2991/978-94-6239-648-7_43How to use a DOI?
Keywords
UAV; Visual Enhancement; System Algorithms; Target Tracking
Abstract

Unmanned aerial vehicle target tracking is one of the key areas of study in the field of computer vision and intelligent control, widely used in aerospace, intelligent driving, security surveillance, smart agriculture, and search and rescue, which can also carry out aerial multi-view multi-platform long-distance real-time dynamic object tracking through its own high maneuverability, good adaptability to the environment, etc. Although UAVs (Unmanned Aerial Vehicles, UAVs) have good maneuverability, they also have shortcomings; the complex climate can easily cause target deformation, partial occlusion, similar objects interfering, and even illumination changes will lead to poor performance of visual system, the amount of data of UAV on board is huge, and then the computing power of the onboard UAV is small, difficult to achieve high precision algorithm for real-time performance and high energy consumption. Therefore, this paper designs a UAV target tracking system that integrates multimodal visual enhancement methods to utilize multimodal perception and realize scene-adaptive switching, as well as lightweight feature fusion, thereby reducing computational resources, improving tracking accuracy, and enhancing robustness under complex backgrounds. The system also leverages the latest communication technology.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
Series
Advances in Computer Science Research
Publication Date
24 April 2026
ISBN
978-94-6239-648-7
ISSN
2352-538X
DOI
10.2991/978-94-6239-648-7_43How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Tianlin Guo
PY  - 2026
DA  - 2026/04/24
TI  - Unmanned Aerial Vehicle Target Tracking Systems in Complex Environments Based on Visual Enhancement Technology
BT  - Proceedings of the International Workshop on Advances in Deep Learning for Image Analysis and Computer Vision (IWADIC 2025)
PB  - Atlantis Press
SP  - 388
EP  - 399
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-648-7_43
DO  - 10.2991/978-94-6239-648-7_43
ID  - Guo2026
ER  -