摘要
运动人体目标的跟踪一直是视频监控中研究的重点。本文主要侧重柔性目标变形的方面,以HSI颜色模型进行模板的学习,在当前帧中得到模板,并且统计每一帧图像的信息量,然后在一下帧中进行Kalman预测。将预测到的区域与模板比较判断之后再决定是否更新模板,减少了一定的计算量,为了约束窗口的变化,引入信息量的概念,信息量由HSI颜色空间的I的特征点计算得到。这样,一直更新模板和窗口直至准确有效地跟踪人体目标。实验表明,在人体发生较大形变的过程中,会持续的跟踪人体,不会发生跟踪丢失的问题。
The human tracking is the key in the video surveillance.This text focuses on non-rigid objects,learning based on the HSI color model template.Each pixel of the template is modeled using two components with H and S.Get template from the current frame,statistic the information of every frame,and predict in the next frame using Kalman filter.Decide whether to update the template after comparing the forecast region and the template,reducing the amount of calculation.And for restraining the tracking window,information which is calculated from the color I is introduced.After that,the template and the window will be updated.The experimental results show that the proposed method achieves continuously tracking,and resolve the problem with the object disappeared.
出处
《光电工程》
CAS
CSCD
北大核心
2012年第11期101-108,共8页
Opto-Electronic Engineering
