高技术通讯2018，Vol.28Issue(3)：207-213,7.DOI:10.3772/j.issn.1002-0470.2018.03.003
基于卷积神经网络的目标跟踪算法综述
Review of object tracking based on convolutional neural networks
摘要
Abstract
The article points that object tracking is an important research topic in the field of machine vision , and it is widely used in national defense , transportation and other fields .With the development of training data and hard-ware, more and more researchers are applying the technique of deep learning to visual tracking .Recently, a large number of tracking algorithms based on deep learning are proposed .Compared with the traditional machine learning methods, the techniques using convolution neural networks with multiple hidden layers have more powerful capaci -ties of feature learning and feature expression .Then, it analyzes the difficult problems in object tracking and the possibility of using convolution neural networks to solve object-tracking problems .Furthermore , the development of convolution neural networks in visual tracking is reviewed , and the latest results of applying convolution neural net-works to visual target tracking are summarized and analyzed .Finally, the future development of convolutional neu-ral networks in object tracking is discussed .关键词
卷积神经网络(CNN)/深度学习/目标跟踪/机器视觉Key words
convolutional neural networks (CNN)/deep learning/object tracking/machine vision引用本文复制引用
胡硕,赵银妹,孙翔..基于卷积神经网络的目标跟踪算法综述[J].高技术通讯,2018,28(3):207-213,7.基金项目
国家自然科学基金(61741418)资助项目. （61741418）
