计算机工程与应用2019，Vol.55Issue(10)：16-29,14.DOI:10.3778/j.issn.1002-8331.1810-0170
基于深度学习的视频跟踪研究进展综述
Survey of Research Progress of Video Tracking Based on Deep Learning
摘要
Abstract
In recent years, deep learning has developed rapidly. It has overturned the design of algorithms for speech rec-ognition, image classification and text understanding. Because of its strong feature extraction ability, deep learning has achieved outstanding results in the field of image recognition. However, the combination of deep learning and video sur-veillance is not much. Because the depth model has a multi-layer network structure and the complexity of the algorithm is large, it takes time to train and update the model, and it is difficult to meet the real-time requirements. This paper reviews the development history of deep learning, and introduces the main model of deep learning in the last 10 years. Then, this paper discusses the target tracking algorithm based on deep learning and points out the advantages and disadvantages of each algorithm. Finally, the current problems and development prospects in this field are summarized and prospected.关键词
深度学习/视频跟踪/卷积神经网络/递归神经网络/自编码器Key words
deep learning/video tracking/convolutional neural network/recurrent neural network/autoencoder分类
信息技术与安全科学引用本文复制引用
戴凤智,魏宝昌,欧阳育星,金霞..基于深度学习的视频跟踪研究进展综述[J].计算机工程与应用,2019,55(10):16-29,14.基金项目
国家社会科学基金(No.15ZDB102). （No.15ZDB102）
