Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院
Journal:INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2017
Key Words:Unmanned aerial vehicles Target tracking CamShift
Abstract:Unmanned aerial vehicles (UAVs) equipped with monitoring systems have played an important role in various fields in recent years. An object tracking algorithm is necessary in order to process information in the wide range of UAV videos. CamShift algorithm is outstanding as its efficient pattern matching and fast convergence. This paper presents an excellent method based on CamShift to implement precise target tracking in UAV videos. This method integrates multi-feature fusion (MF), CamShift, and Kalman filter (KF) called the MF-KF-Camshift algorithm. Experimental results show that the method achieves great performance in dealing with different scenes and meets the real-time requirements.
ISSN No.:0302-9743
Translation or Not:no
Date of Publication:2017-01-01
Co-author:Zhao, Chang,Zheng, Huiting
Correspondence Author:Yuan Jiabing
Professor
Supervisor of Doctorate Candidates
Main positions:图书馆馆长
Alma Mater:南京航空航天大学
Education Level:南京航空航天大学
Degree:Doctoral Degree in Engineering
School/Department:College of Computer Science and Technology
Business Address:南京航空航天大学将军路校区计算机科学与技术学院院楼318
Contact Information:邮箱:jbyuan@nuaa.edu.cn 联系电话:13805165286
Open time:..
The Last Update Time:..