A Fast Hyperspectral Object Tracking Method Based on Channel Selection Strategy

Yifan Zhang, Xu Li, Feiyue Wang, Baoguo Wei, Lixin Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

15 引用 (Scopus)

摘要

Hyperspectral object tracking aims to take advantage of the rich spatial and spectral information in hyperspectral videos to effectively improve the robustness and accuracy of object tracking. Compared with color videos, hyperspectral videos have huge amount of data bringing a challenge to the efficiency of object tracking. We propose a fast hyperspectral object tracking method based on channel selection strategy. The strategy considers the spatial and spectral changes of local regions in the frame image and selects only three channels fed to tracker to speed up. The experimental results show that our method reaches 11.5 FPS on the dataset of Hyperspectral Object Tracking Challenge, which is faster than the state-of-the-art methods.

源语言英语
主期刊名2022 12th Workshop on Hyperspectral Imaging and Signal Processing
主期刊副标题Evolution in Remote Sensing, WHISPERS 2022
出版商IEEE Computer Society
ISBN(电子版)9781665470698
DOI
出版状态已出版 - 2022
活动12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022 - Rome, 意大利
期限: 13 9月 202216 9月 2022

出版系列

姓名Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
2022-September
ISSN(印刷版)2158-6276

会议

会议12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022
国家/地区意大利
Rome
时期13/09/2216/09/22

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