井下目标跟踪与测距方法研究

Target Tracking and Ranging Method in Underground Mine

矿井下存在某些危险区域,这些区域不允许工人在未采用安全措施的情况下进入,然而由于一些环境或人为因素,使得常用的警示标志不够有力,导致了井下事故的发生。因此,文章介绍了一种采用基于计算机视觉的自动检测方法检测工人是否进入危险区域的方法,该方法首先使用核相关滤波算法KCF(Kernel Correlation Filter)跟踪目标,然后利用双目视觉原理对跟踪的目标进行测距,同时利用Kalman滤波算法优化所得到的距离信息,使得测距方法对于遮挡目标有一定的鲁棒性,保证目标在危险区域之外。井下目标跟踪与测距方法具有价格低廉,计算量少,测量距离范围大,测距准确度高等优点。

There are certain hazardous areas in underground mine that do not allow workers to enter without safety measures,however,due to some environmental or human factors,the commonly used warning signs are not strong enough,which leads to underground accidents. Therefore,an automatic detection method based on computer vision is used to detect whether workers enter dangerous areas. First,a kernel correlation filter algorithm KCF( Kernel Correlation Filter) is used to track the target,then the tracked target is measured with binocular vision principle. Simultaneously the Kalman filter algorithm is applied to optimize the obtained distance information,which make the ranging method a certain robustness for the occlusion target,and ensure that the target is outside the dangerous area. The underground target tracking and ranging method has the advantages of low price,low calculation amount,large measuring distance range and high accuracy of ranging.