首页 | 本学科首页   官方微博 | 高级检索  
     

基于LBP与核相关滤波器的运动目标跟踪算法
引用本文:齐永锋,王梦媛.基于LBP与核相关滤波器的运动目标跟踪算法[J].红外技术,2019,41(6):572-576.
作者姓名:齐永锋  王梦媛
作者单位:西北师范大学计算机科学与工程学院,甘肃兰州,730070;西北师范大学计算机科学与工程学院,甘肃兰州,730070
基金项目:甘肃省高等学校科研项目
摘    要:针对核相关滤波器在复杂光照条件下出现的跟踪不稳定的现象,提出一种基于LBP(local binary pattern)与核相关滤波器的运动目标跟踪算法。在传统算法上增加LBP处理方法,降低光照对特征提取的影响,进而提高核相关滤波器算法在跟踪过程中对目标信息的采集精准度。实验表明,与经典的核相关滤波器跟踪算法相比,基于LBP与核相关滤波器的运动目标跟踪算法在复杂光照的情况下的跟踪性能有明显提升,能较好应用于实时场景中去,是一种稳定的目标跟踪算法。

关 键 词:核相关滤波器  LBP  特征提取  实时处理  机器学习

Moving Target Tracking Algorithm Based on LBP and Kernel Correlation Filter
QI Yongfeng,WANG Mengyuan.Moving Target Tracking Algorithm Based on LBP and Kernel Correlation Filter[J].Infrared Technology,2019,41(6):572-576.
Authors:QI Yongfeng  WANG Mengyuan
Affiliation:(College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China)
Abstract:A moving target tracking algorithm based on LBP(Local binary pattern) and kernel correlation filter is proposed for kernel correlation filter when the tracking instable under complex illumination. In the traditional algorithm the LBP processing method is added to reduce the effect of light on the feature extract, and then the accuracy of the acquisition of the target information in the tracking process is improved. Experiments show that compared with the classical kernel correlation filter tracking algorithm, the moving target tracking algorithm based on LBP and kernel correlation filter can significantly improve the tracking performance when facing complex illumination. It can be used in real time scene and is a stable target tracking algorithm.
Keywords:kernel correlation filter  LBP  feature extract  real-time processing  machine learning
本文献已被 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号