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Arabian Journal for Science and Engineering
Erschienen in: Arabian Journal for Science and Engineering 2/2023

21.07.2022 | Research Article-Computer Engineering and Computer Science

Complexity Metric Methodology of Infrared Image Sequence for Single-Object Tracking

verfasst von: Feng Xie, Minzhou Dong, DongSheng Yang, Jie Yan, XiangZheng Cheng

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 2/2023

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Abstract

The complexity metric of infrared image sequences is crucial to the prediction and evaluation of single-object tracker performance, and it is a research hotspot in the field of computer vision. However, the accuracy and comprehensiveness of the existing complexity metrics are limited. In this paper, an effective method is proposed to quantify the single-object tracking difficulty of infrared image sequences. First, based on the classification and analysis of trackers, the influencing factors of infrared target tracking are summarized. Then, five metrics combining deep features and shallow features are proposed to characterize the complexity of infrared image sequences. Finally, a synthesis complexity metric is designed for comprehensive evaluations of infrared image sequences. Experimental results indicate that our method performs better than traditional methods on comprehensiveness, and the proposed metrics can more accurately reflect the performance of trackers on different infrared image sequences.
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Metadaten
Titel
Complexity Metric Methodology of Infrared Image Sequence for Single-Object Tracking
verfasst von
Feng Xie
Minzhou Dong
DongSheng Yang
Jie Yan
XiangZheng Cheng
Publikationsdatum
21.07.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
Arabian Journal for Science and Engineering / Ausgabe 2/2023
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-022-07090-z

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