在线多目标视频跟踪算法综述

摘要

视频多目标跟踪是计算机视觉领域重要的研究课题之一,不论是在军用还是民用都有广泛应用.目前对单目标的跟踪算法研究已经相当成熟,但对于多目标跟踪的研究还处于发展阶段.重点研究了多目标跟踪过程中的四个重要阶段:特征提取、检测器、数据关联、跟踪器.特征提取阶段详细介绍了目前主流的特征提取方法以及各个方法之间的优缺点;检测器阶段首先详细介绍了目标外观模型在具体应用场景中的跟踪效果,接着对基于检测跟踪的多目标跟踪算法和基于深度学习的多跟踪算法进行了分析;跟踪器阶段分别介绍了目标运动模型的建立和利用不同跟踪器混合的多目标跟踪算法;数据关联阶段分别介绍了基于能量最小化的多目标跟踪以及常用的数据关联算法.接着,介绍了目前主流的数据集以及评测方法;最后对多目标跟踪未来的发展进行了思考和展望.%Video multi-object tracking is one of the important research topics in the field of computer vision,which is widely used in military and civil areas.At present,the research of single object tracking algorithm has quite mature,but for multi-object tracking of the research is still ongoing.This paper focuses on four important stages in the multi-object tracking process:feature extraction,detector,data association and the tracker.The feature extraction part introduces the current meth-ods of feature extraction,as well as the merits and demerits of each method;In the stage of detection,the tracking effect of the object appearance model in specific applications is described,and then we analyze the multi-object tracking algorithm based on detection and tracking as well as the multi-object tracking algorithm based on deep learning;In the tracking phase, the establishment of object motion model and multi-object tracking with different tracker hybrid algorithm are introduced;During the stage of data correlation,we introduce the multi-object tracking based on energy minimization and commonly used data association algorithm,respectively.Then we introduce the current mainstream datasets and evaluation methods.Finally, the future development of the multi-object tracking is discussed and forecasted.