多目标跟踪的对象初始化综述

Object Initialization in Multiple Object Tracking:A Review

对象初始化方法决定了如何对待多目标跟踪问题,与后续的多目标跟踪效果直接相关。不同的对象初始化方法能够确定不同的多目标跟踪框架,每一种框架都提供一种解决问题的思路,使得多目标跟踪的对象初始化问题具有巨大的研究前景。目前关于多目标跟踪中的对象初始化方法的综述性文献较少或缺乏系统性的对象初始化概述,因此文中从多假设跟踪方法、网络流方法、深度学习方法和主题发现方法4个方面对多目标跟踪的对象初始化方法进行分析。系统地阐述了不同多目标跟踪框架下的任务转换和对象映射问题,汇总了多目标跟踪的对象初始化方法。

Object initialization method determines how to treat the multi-object tracking problem,being directly related to the subsequent tracking result.Different object initialization methods confirm different multi-object tracking frameworks and each framework provides a way to solve the problem,which makes the object initialization of multi-object tracking a huge research prospect.Currently there are few literature on object initialization methods of multi-target tracking,or lacks a systematic overview of object initialization.Therefore,we analyze the object initialization methods on four aspects:multi-hypothesis tracking,network flow,deep learning and topic discovery.We systematically expound the task conversion and object mapping problems under different multi-object tracking frameworks,and summarize the object initialization methods for the multi-object tracking.