Multi-Target Association for UAVs Based on Fused Topology and Visual Features

In this letter, we propose a novel multi-target association algorithm that fuses topological and visual features, and this algorithm improves target discrimination. The fused features are first constructed, and then a similarity calculation method is proposed to aggregate neighbor similarities to the central node based on topological similarity, which can be iterated several times to enhance the differentiation between targets. The experimental results demonstrate the advantages of the proposed algorithm. Github: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/SupersPig/FTVF</uri>

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3559825
Citations
3
Primary Topic
Advanced Image and Video Retrieval Techniques
Type
article
Field-Weighted Citation Impact
3.83
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article

Multi-Target Association for UAVs Based on Fused Topology and Visual Features

Lizhen Wu, Xudong Li, M. Yuan, Yifeng Niu
3 citations
IEEE Signal Processing Letters
Advanced Image and Video Retrieval Techniques
3.83
article

Multi-Target Association for UAVs Based on Fused Topology and Visual Features

Lizhen Wu, Xudong Li, M. Yuan, Yifeng Niu
article en
3 citations

Abstract

In this letter, we propose a novel multi-target association algorithm that fuses topological and visual features, and this algorithm improves target discrimination. The fused features are first constructed, and then a similarity calculation method is proposed to aggregate neighbor similarities to the central node based on topological similarity, which can be iterated several times to enhance the differentiation between targets. The experimental results demonstrate the advantages of the proposed algorithm. Github: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/SupersPig/FTVF</uri>

IEEE Signal Processing LettersVol. 32
National University of Defense Technology (CN)
Openalex Percentile: Top 7%
Advanced Image and Video Retrieval Techniques
3.83
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