基于随机蕨丛的双层视频分割算法

Bilayer Video Segmentation Based on Random Ferns

提出一种基于随机蕨丛的双层视频分割算法,实现对单目视频的自动分割.算法在对视频运动特征进行聚类的基础上,构造视频运动特征字典,通过随机蕨丛对运动特征进行建模.在此基础上利用条件随机场约束视频颜色、运动特征以及邻域关系,通过graph-cut算法求解出全局最优的分割结果.在实验中采用多种环境的视频数据对本文算法的有效性进行测试,并与其他分割算法的结果进行比较.

A random ferns based method is proposed for bilayer video segmentation with the capability of segmenting monocular video automatically. Motion feature dictionary is constructed by clustering the motion features of the video, and the motion features are modeled by random ferns. The video colors, motion features and neighboring relationships are constrained by using conditional random fields. The graph-cut algorithm is adopted for solving globally optimal segmentation results. The experimental results demonstrate the validity of the proposed algorithm, and the results of the proposed method are compared with other algorithms on different video data.