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摘要: 与现有的视频运动对象分割算法不同, 本文提出一种新的基于吉布斯 (Gibbs) 随机场模型的视频运动对象的分割算法, 该算法将运动对象的运动场作为主分割信息, 空间像素值的一致性作为次要分割信息. 该算法首先对运动矢量场进行累加和滤波处理;然后在 Gibbs 运动场模型的势能函数的定义中引入空间相关影响因子, 采用最大后验概率的方法进行分割;最后细化运动对象边缘. 对多个视频序列的测试, 实验结果表明该算法比现有基于光流的分割算法更准确的分割运动对象.Abstract: In the proposed algorithm, different from other video object segmentation algorithms, the motion vector filed is mainly analyzed for segmentation and the spacial relativity is assistant information for segmentation. Firstly, the motion vectors are processed by accumulation and median filter. Secondly, the spacial relativity variable is defined in potential function and maximum a posteriori probability (MAP) is used to segment video moving object. Lastly, the edge of video moving object is made more exactly. The experimental results for different video sequences show the proposed algorithm has a better veracity of segmentation compared to other algorithms.
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Key words:
- Segmentation /
- moving object /
- Gibbs random field
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