MULTI-FEATURES INTEGRATION BASED HYPERSPECTRAL VIDEOS TRACKER

被引：25
作者：
Zhang, Zhe [1 ]
Qian, Kun [2 ,3 ]
Du, Juan [1 ]
Zhou, Huixin [1 ]
机构：
[1] Xidian Univ, Lab Optoelect Imaging & Image Proc, Xian 710071, Peoples R China
[2] Jiangnan Univ, Sch Artif Intelligence & Comp Sci, Wuxi 214122, Jiangsu, Peoples R China
[3] Jiangsu Key Lab Media Design & Software Technol, Wuxi 214122, Jiangsu, Peoples R China
来源：
2021 11TH WORKSHOP ON HYPERSPECTRAL IMAGING AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2021年
关键词：
Target tracking; Hyperspectral video; Multi-features; Correlation filter; Deep learning;
D O I：
10.1109/WHISPERS52202.2021.9484029
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Most target tracking is over visible videos, but in a challenging scene, tracking targets with the same appearance is very difficult on visible videos, due to the limitation of grayscale and color information. Therefore, we use Hyperspectral Videos (HSVs) with rich spectral information for target tracking to distinguish similar targets. In this paper, a multi-features integration based tracking method is proposed over HSV. The feature maps are generated by Histogram of Gradient (HOG) and pretrained VGG-19 network, and then kernelized correlation filter framework is utilized to detect target over HSVs. Specially, More information of spatial, spectral and temporal are all used to extract useful features, and these feature can track the target that can not be tracked in visible videos. The experimental results on HSVs show that the proposed method has better performance than the three existing tracking methods with hyperspectral information.
引用
收藏
页数：5
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