Paper Title :Object-Tracking: A Comparative Analysis of Visual Tracking Algorithms
Author :Yan-Ru Lee, Fu-Shin Lee
Article Citation :Yan-Ru Lee ,Fu-Shin Lee ,
(2024 ) " Object-Tracking: A Comparative Analysis of Visual Tracking Algorithms " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 103-110,
Volume-12,Issue-9
Abstract : This paper surveys visual object-tracking algorithms, covering traditional, deep learning-based, and hybrid
approaches. We analyze the advantages and limitations of clustering, optical flow, correlation filters, Siamese Networks,
GANs, Transformers, and the hybrid TLD algorithm. Based on prior recent research, this paper provides an overview of the
current state of object-tracking algorithms, offering insights into their effectiveness and applicability in real-world scenarios.
Keywords - Mean Shift,Object-tracking, Visual tracking algorithms, Optical flow, Siamese Networks, Transformers
Type : Research paper
Published : Volume-12,Issue-9
Copyright: © Institute of Research and Journals
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Published on 2025-01-08 |
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