监控视频运动目标的频繁轨迹模式挖掘

运用数据挖掘的方式分析运动轨迹数据在目前可以说是一种尝试。基于传统数据挖掘方法Apriori的思想,提出了一种监控视频运动目标的频繁轨迹模式挖掘算法。首先以特征点表示连续的运动目标轨迹,然后设计了一种轨迹相似度测量机制,最后基于相似度测量获得的轨迹段频率,将Apriori挖掘算法应用到2D运动轨迹数据,从中发现频繁轨迹隐含的一些感兴趣模式。实际的和人工生成的轨迹数据实验表明了算法的正确有效性。

Mining Frequent Trajectory Patterns of Moving Objects from Surveillance Video

It is only a tentative attempt to analyze motion trajectory data in the data mining style.This paper proposes an algorithm based on Apriori,a conventional data mining method,for mining frequent trajectory patterns of moving objects from surveillance video.Firstly,feature points are extracted for presenting continuous trajectories.Then a trajectory similarity measure is designed to obtain the frequency of trajectories.Finally,based on the values,Apriori algorithm is applied to automatic finding of interesting patterns in 2D object trajectories.Experiments on real life and man-made trajectory data set show the validity of the algorithm.