DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-12,Issue-9 ( Sep, 2024 ) | |||||||||
Paper Title |
Object-Tracking: A Comparative Analysis of Visual Tracking Algorithms | |||||||||
Author Name |
Yan-Ru Lee, Fu-Shin Lee | |||||||||
Affilition |
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Pages |
103-110 | |||||||||
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 | |||||||||
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