Computer Science ›› 2015, Vol. 42 ›› Issue (8): 86-89.

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Moving Target Detection Using Fusion of Visual and Thermal Video

ZHANG Sheng, YAN Yun-yang and LI Yu-feng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In outdoor environments,visible light camera can get rich texture and spectral information in the scene,but they are greatly influenced by illumination changes.On the contrary,thermal infrared camera is not sensitive to light and it is still able to work effectively under night.But the thermal infrared images have less color information and lower contrast.In order to make full use of the complementary information of infrared and visible light for detection target,a novel method based on Gaussian mixture model with RGBT was proposed for moving target detection more accurately and robust.This method adds the thermal infrared images as the fourth component to the conventional Gaussian mixture model to improve the positive detection rate.Meanwhile,the shadow removal algorithm is introduced to reduce the impact of shadows caused by the ambient illumination changes,so the robustness of proposed method is enhanced.Experimental results show that the suggested method not only achieves the higher detection accuracy and more complete object,but also meets the real-time requirements better compared to the conventional Gaussian mixture models.

Key words: Moving target detection,Thermal video,Visible video,Data fusion,Gaussian mixture model

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