基于分层光流的煤矿井下运动目标跟踪算法

An algorithm for moving targets tracking in coal mine underground based on layered optical flow

针对煤矿井下视频序列高噪声、运动目标繁多、目标交错等特点,提出了一种基于分层光流法的矿井运动目标跟踪算法。首先对相邻两帧视频序列采用帧差法确定多个初始目标跟踪模版;然后采用SUSAN角点检测提取模版内的特征点;最后运用改进的分层光流法进行目标检测和跟踪,并在跟踪过程中对模版进行更新。该算法实现了煤矿井下多目标运动物体的稳定跟踪,并能解决目标部分遮挡问题。实验和仿真结果证实了该算法的有效性。

In view of characteristics of high noise, amounts of moving targets and target crisscross of video sequence in coal mine underground, an algorithm for moving targets tracking in coal mine underground based on layered optical flow was proposed. Firstly, the initial target tracking templates was determined by using the difference method between two adjacent video sequence frames, and then the feature points of the template was extracted by SUSAN corner detection. Finally, target detection and tracking was realized by improved layered optical flow algorithm, and the template was update in the process of tracking. The algorithm realizes stable tracking of multi-object moving object in coal mine underground, and can solve the problem of partial occlusion target. The experimental and simulation results confirm the effectiveness of the algorithm.