Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Review on Target Tracking Algorithm Based on Deep Learning

Authors
Shihao Tao1, *
1School of Information and Communication Engineering, Nanjing Institute Of Technology, Nanjing, China
*Corresponding author. Email: x00208201127@njit.edu.cn
Corresponding Author
Shihao Tao
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_31How to use a DOI?
Keywords
Object tracking; Deep Learning; Deep Reinforcement Learning
Abstract

Target tracking is a crucial research area in computer vision, with increasing demand for real-time monitoring and intelligent interaction. Algorithms for target tracking have evolved from traditional feature matching methods to modern deep neural networks, reinforcement learning, and model-based approaches. These algorithms are not only applied in video surveillance but also promote the development of drone tracking, autonomous driving, human-computer interaction, behavior analysis, and other fields. However, target tracking still faces challenges, such as interference from lighting intensity, environmental objects, and cluttered backgrounds, as well as the need for real-time tracking and accurate identification of multiple similar targets. This study focuses on the problem of target tracking and proposes a solution. Specifically, we adopt deep neural networks and reinforcement learning to improve the accuracy and real-time performance of target tracking. Experimental results indicate that our algorithm can accurately track targets in various scenarios and exhibits good robustness and real-time performance.

Copyright
© 2024 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 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_31
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_31How to use a DOI?
Copyright
© 2024 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  - Shihao Tao
PY  - 2024
DA  - 2024/02/14
TI  - Review on Target Tracking Algorithm Based on Deep Learning
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 283
EP  - 296
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_31
DO  - 10.2991/978-94-6463-370-2_31
ID  - Tao2024
ER  -