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作 者:樊翠红 孔祥魁 向华[1] FAN Cuihong;KONG Xiangkui;XIANG Hua(Yangtze University,Jingzhou Hubei 434023,China)
机构地区:[1]长江大学,湖北荆州434023
出 处:《激光杂志》2022年第9期71-75,共5页Laser Journal
基 金:中央引导地方科技发展专项资金项目(No.2018ZYYD045);湖北省教育厅项目(No.2020Y039);长江大学2019年度课题(No.2019YSH07);长江大学教师教育研究中心创新基金项目(No.2020JSJYZX04)。
摘 要:针对当前运动轨迹自动跟踪方法存在的缺陷性,如易跟丢运动目标、实时跟踪性能差等,为了提高运动轨迹自动跟踪精度,获得更加理想的运动轨迹自动跟踪结果,设计了基于红外传感技术的运动轨迹自动跟踪方法。首先通过红外传感器采集运动目标轨迹视频数据,并对运动轨迹视频进行分帧处理,得到运动轨迹图像,然后从图像中提取运动轨迹初始状态,并引入改进Kalman滤波算法对运动目标轨迹进行跟踪,最后进行了运动目标轨迹仿真模拟实验,实验结果表明,本方法较好地克服了当前运动目标轨迹跟踪方法存在的弊端,运动目标轨迹跟踪精度超过了90%,运动目标轨迹跟踪时间的平均值控制在25 ms以内,相对于对比方法,本方法明显改善了运动目标轨迹跟踪的效果,验证了本方法用于运动目标轨迹跟踪的优越性。In view of the shortcomings of the current motion trajectory automatic tracking method,such as easy to follow and drop the motion target,poor real-time tracking performance,etc.,in order to improve the automatic tracking accuracy of the motion trajectory and obtain more ideal motion trajectory automatic tracking results,the motion trajectory automatic tracking method based on infrared sensing technology is designed.Firstly,the motion target trajectory video data is collected by the infrared sensor,and the motion trajectory video is framed to obtain the motion trajectory image,and then the initial state of the motion trajectory is extracted from the image,and the improved Kalman filtering algorithm is introduced to track the trajectory of the moving target,and finally the motion target trajectory simulation experiment is carried out.The experimental results show that the proposed method better overcomes the shortcomings of the current motion target trajectory tracking method,the track tracking accuracy of the motion target exceeds 90%,and the average value of the track tracking time of the motion target is controlled within 25 ms,compared with the comparison method,the proposed method significantly improves the effect of the trajectory track tracking of the moving target,and verifies the superiority of the proposed method for the trajectory tracking of the motion target.
关 键 词:红外感技术 运动目标 移动轨迹 Kalman滤波算法 视频分帧处理
分 类 号:TN919.8[电子电信—通信与信息系统]
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