夜间边境非法越界热成像智能监测方法

国家边界线夜间非法越境监测和报警是一个重要的研究课题，目前存在的监控系统智能性低、误检率高、计算时间慢。为了实现智能监测，提出了一种热成像智能监测方法。首先使用高斯背景建模提取前景目标，使用HOG+SVM的方法对前景目标进行越界人检测；为了消除动物的干扰，利用STC算法进一步跟踪并分析目标速度和运动轨迹。实验结果表明，设计的方法提高了越界人检测的准确率，检测时间提高到60 ms左右，满足了现场应用。

Thermography Intelligent Monitoring Method for Illegal Person Crossing the Border at night

Detecting illegal Person crossing national boundary line at night is an important research topic. The current monitoring system has disadvantage of low intelligence, high false detection rate and slow calculation time and so on. In order to achieve intelligent monitoring, a thermography intelligent illegal person monitoring method is proposed. Firstly, the foreground object is extracted using Gaussian background modeling in order to decrease the processed image size. The HOG and SVM are combined to detect the running target. Then, in order to eliminate the false alarm caused by animal interference, the STC algorithm is used to get the speed and trajectory of detected person or animal and judge illegal cross-border person according to running trajectory. The experimental results show that this method not only improves the illegal person detection accuracy, but also every frame average detection time is only less than 60 ms which satisfies the actual application requirement.