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自适应权值的MRF分割与跟踪方法

齐美彬,杨立宾,蒋建国(合肥工业大学计算机与信息学院, 合肥 230009; 安全关键工业测控技术教育部工程研究中心,合肥 230009)

摘 要
提出一种基于自适应权值的区域马尔可夫随机场(MRF)分割与跟踪的方法,该方法利用了相邻像素区域的空间相关性,自适应更新系统能量函数中的参数β,可以更准确地分割出运动目标,在此基础上建立分片积分直方图特征模板,并结合Kalman预测与目标运动方向等信息,进一步提高算法准确性,实现目标匹配跟踪。实验结果表明,本文算法在部分遮挡、光线变化等情况下,能准确实现运动目标分割与跟踪。
关键词
MRF segmentation and tracking algorithm based on adaptive weight

Qi Meibin,Yang Libin,Jiang Jianguo(Hefei University of Technology)

Abstract
The paper proposes a segmentation and tracking method based on adaptively weighted Markov random field (MRF).By using spatial relativity of the adjacent pixel regions, this method adaptively updates the system energy function parameter β, and makes object segmentation more accurate. On this condition, the fragments-based integral histogram feature template is established. And Kalman prediction method is combined with object motion information to improve the algorithm’s accuracy and implement matching and tracking. Experiment results proved that this algorithm can accurately settle with the problem of objects segmentation and tracking problem under the case of partial shelter,and illumination change.
Keywords
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