多目标跟踪算法的研究与应用

Research and Application on Multi—target Tracking Algorithm

将多目标跟踪算法用于水中絮体颗粒的跟踪,提出了一种代价函数结合改进MHT的算法,对出现异常的絮体颗粒用改进MHT算法跟踪,并通过分析絮体颗粒运动特性修正了改进MHT算法,有效解决了跟踪过程中出现的轨迹交叉、轨迹合并等情况,这样在保证跟踪精度的基础上又提高了跟踪速度;同时,采用跟踪絮体颗粒得到颗粒的沉淀速度信息来评价水处理混凝的效果,自动控制混凝剂的加注,从而达到自来水水质检测和净化的目的。

This paper presents a method of Multi-target tracking algorithm based on a cost function and improved multiple hypothesis tracking （MHT） algorithm to track floes in the water, then makes use of the improved MHT algorithm to track unusual targets, and revises the improved MHT algorithm through analyzing the motion traits, acquires excellent effect on solving the problems of crossed track and merged track. Experimental results prove that it can accurately track objects and has satisfying velocity. This method has been successfully used in the detection of sedimentation velocity of flocculent particles and automatic floeeulation control system, in order to detect the water quality.