摘要
为了提高红外与可见光视频运动目标跟踪性能,提出了高精度红外与可见光视频运动目标智能跟踪方法。首先确定红外与可见光视频运动目标特征的权重值,并计算运动目标特征的稀疏程度,提取目标特征,采用卡尔曼滤波算法确定了运动目标的具体位置,采用粒子滤波实现运动目标跟踪算法,最后采用篮球的红外与可见光视频运动目标作为测试对象,结果表明,本文方法不仅可以提高红外与可见光视频中运动目标的跟踪准确率,还可以降低运动目标的跟踪误差,大大提升了运动目标的跟踪性能。
In order to improve the performance of infrared and visible video moving target tracking,a high-preci-sion intelligent tracking method for infrared and visible video moving target is proposed.Firstly,the weight value of the infrared and visible video moving target features is determined,and the sparsity degree of the moving target feature is calculated,and the target feature is extracted.The specific position of the moving target is determined by Kalman filter algorithm,and the moving target tracking algorithm is realized by particle filter.Finally,the infrared and visible video moving target of basketball is used as the test object This method can not only improve the tracking accuracy of moving target in infrared and visible video,but also reduce the tracking error of moving target,which greatly improves the tracking performance of moving target.
作者
许淑贤
赵志梅
XU Shuxian;ZHAO Zhimei(Guilin University of Technology,Guilin Guangxi 541004,China)
出处
《激光杂志》
CAS
北大核心
2021年第8期192-195,共4页
Laser Journal
基金
广西自然科学基金(No.2016GXNSFBA380094)。
关键词
红外与可见光
运动目标
智能跟踪
特征提取
跟踪算法
infrared and visible light
moving target
intelligent tracking
feature extraction
tracking algorithm
