基于贝叶斯原理的视觉多目标跟踪研究  

Multi-Objects Vision Tracking Based on Bayesian Theorem

作　　者：高敬惠[1] 姜子敬[1] 田金慷[1] 刘国丽[1] 

机构地区：[1]河北工业大学廊坊校区计算机系,河北065000

出　　处：《微计算机信息》2007年第21期220-221,206,共3页Control & Automation

基　　金：河北省教育厅科学研究项目(2004416)基于小波分析的视频图像压缩算法研究

摘　　要：阐述了基于贝叶斯原理的粒子滤波技术。推导了粒子滤波的过程,将状态区域中包含的图像部分的直方图作为检测量与参考目标直方图比较,并在滤波过程中更新,得出目标最大后验估计。使用窗口平均法确定目标的最终坐标。在实验中,对单一及多个目标进行跟踪,结果证明,本文方法效果良好。Propose particle filter technology based on Bayesian theorem. List the process of particle filter. The histogram in the image region of the state is regarded as measurement object that is eompared with the referenee image histogram. It is updated in the filter processing to obtain the optimized posteriori probabilities. The robust mean teehnique is applied to aseertain the objects＇ positions. In the experiments, both single and multi objects are traeked and the results show that the method in the paper is effieient.

关 键 词：贝叶斯理论 多目标跟踪 粒子滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]