Research and Implementation of Target Tracking Algorithm Based on Convolution Neural Network

被引:0
作者
Zhang, Li Jun [1 ]
Wang, Chen [1 ]
Jin, Xing [1 ]
机构
[1] China Univ Geosci, Sch Automat, Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan 430074, Hubei, Peoples R China
来源
2018 37TH CHINESE CONTROL CONFERENCE (CCC) | 2018年
关键词
Regional convolutional neural network; Target tracking; Kalman filtering;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Video target tracking is an important research topic in computer vision, and has been widely used in video surveillance, robot, human-computer interaction and so on. The emergence of large data age and the emergence of in-depth learning methods provide a new opportunity for the study of video target tracking. This paper first analyzes the research problems of video target tracking at present, analyzes the characteristics and trends of video target tracking in the new period, introduces the emerging recursive neural network frame structure, combined with Kalman filter And the experimental results show that the accuracy and robustness of the target tracking based on the convolution neural network algorithm are all good.
引用
收藏
页码:9573 / 9577
页数:5
相关论文
共 5 条
[1]  
Chen YN, 2006, INT C PATT RECOG, P552
[2]   Online selection of discriminative tracking features [J].
Collins, RT ;
Liu, YX ;
Leordeanu, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2005, 27 (10) :1631-1643
[3]   The effect of self-construals on conversational indirectness [J].
Hara, K ;
Kim, MS .
INTERNATIONAL JOURNAL OF INTERCULTURAL RELATIONS, 2004, 28 (01) :1-18
[4]  
Hu W, 2012, IEEE T PATTERN ANAL, V34
[5]   3D Convolutional Neural Networks for Human Action Recognition [J].
Ji, Shuiwang ;
Xu, Wei ;
Yang, Ming ;
Yu, Kai .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (01) :221-231