参数自适应的条件随机场视频分割方法  

Adaptive Parameters Conditional Random Field Video Segmentation Algorithm

作　　者：郑河荣[1] 褚一平[2] 潘翔[1] 

机构地区：[1]浙江工业大学计算机学院,杭州310014 [2]杭州电子科技大学,杭州310032

出　　处：《计算机科学》2010年第5期254-256,294,共4页Computer Science

基　　金：国家自然科学基金(60703001)资助

摘　　要：针对已有算法需要采用一系列参数经验值得到最优视频分割结果的问题,提出根据视频特征自适应地计算视频邻域关系的特征强度函数,构造参数自适应的条件随机场视频分割模型。算法的核心思想是采用视频中像素之间的邻域关系自适应计算各个模型的特征函数,通过条件随机场模型对这些特征能量函数进行约束并利用Gibbs采样算法对该模型进行求解,获得全局优化的分割结果。针对不同环境下的视频分割实验表明,该算法能够很好地逼近最优经验参数所得到的视频分割结果,从而避免定义经验值所导致的算法局限性问题。Aimed at the problem that the video segmentation method based on conditional random fields needs set empirical values to obtain optimal segmentation results,the video segmentation model was proposed to compute adaptively video neighboring relationship feature function by video features and construct adaptive parameters conditional random fields. The core idea of algorithm is to calculate different kinds of model feature function by pixel neighboring relationship in video, these feature energy functions arc constrained by conditional random field model, which is solved via Gibbs sampling algorithm to obtain globally optimal segmentation results. The experiment shows that the results of adaptive parameter algorithm are the same as one of optimal empirical parameters.

关 键 词：视频分割 背景建模 参数自适应 条件随机场 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]