Paper
29 October 2018 Adaptive KCF learning with fused infrared information
Yingqing Huang, Hao Yang, Zhihong Xie
Author Affiliations +
Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 108361C (2018) https://doi.org/10.1117/12.2514677
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China
Abstract
In the land battlefield environment, the tracking of personnel target is mainly affected by the complex environment, like smog, rain, shadows and partial shelter from the woods. These elements make the effect of kernelized correlation filters (KCF) target tracking based on visible light very unsatisfactory, because the brightness, color and rich texture information mainly included in visible light imaging are polluted. The infrared imaging system, due to its sensitivity to heat source, can be perceived in the dark and has low dependence on the surrounding environment. However, limited by its own characteristics, the single infrared imaging system loses some visible light information, such as light intensity, texture and color, and the image resolution is low. Considering the characteristics of visible light and infrared imaging are complementary, it’s reasonable to fuse integral channel features (ICF) of infrared gray image into HOG features of visible light images, and adjust model update rate corresponding to the degree of occlusion of target in the infrared image, to achieve more robust tracking effect.
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Yingqing Huang, Hao Yang, and Zhihong Xie "Adaptive KCF learning with fused infrared information", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108361C (29 October 2018); https://doi.org/10.1117/12.2514677
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KEYWORDS
Infrared radiation

Image fusion

Infrared imaging

Visible radiation

Detection and tracking algorithms

Target detection

Thermal modeling

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