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Fusion of Thermal Infrared and Visible Spectrum Video for Robust Surveillance

机译:融合热红外和可见光谱视频以实现强大的监视

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摘要

This paper presents an approach of fusing the information provided by visible spectrum video with that of thermal infrared video to tackle video processing challenges such as object detection and tracking for increasing the performance and robustness of the surveillance system. An enhanced object detection strategy using gradient information along with background subtraction is implemented with efficient fusion based approach to handle typical problems in both the domains. An intelligent fusion approach using Fuzzy logic and Kalman filtering technique is proposed to track objects and obtain fused estimate according to the reliability of the sensors. Appropriate measurement parameters are identified to determine the measurement accuracy of each sensor. Experimental results are shown on some typical scenarios of detection and tracking of pedestrians.
机译:本文提出了一种将可见光谱视频提供的信息与热红外视频提供的信息相融合的方法,以解决诸如目标检测和跟踪之类的视频处理挑战,以提高监视系统的性能和鲁棒性。使用基于信息融合的有效方法来实现使用梯度信息和背景减法的增强对象检测策略,以处理两个域中的典型问题。提出了一种利用模糊逻辑和卡尔曼滤波技术的智能融合方法来跟踪目标并根据传感器的可靠性获得融合估计。确定适当的测量参数以确定每个传感器的测量精度。在对行人进行检测和跟踪的一些典型场景中显示了实验结果。

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