基于图割框架下视频目标的自动实时提取算法

提出了一种在图割框架下自动实时的前景目标提取算法.通过混合高斯背景建模与基于颜色和局部表观的阴影判别相融合的方法,设置能量函数的数据项,并基于局部二值模型算子构建能量函数的平滑项.利用动态的图割算法,求取目标函数极值,实现视频目标的自动提取.在不同视频上对提出的分割算法进行性能测试,结果表明算法具有较好的分割性能且计算复杂度较低.

Automatic and Real-Time Extraction Algorithm for Video Object Based on a Graph Cut Frame

Abstract： In order to extract foreground object accurately and efficiently in natural scenes, a segmentation algorithm based on the graph cut frame was proposed. First, GMMs background models with the adaptability to the scene change were combined with shadows removal methods using color and local appearance cues to set the data cost in the energy function. Then, the difference based on local binary pattern operator was used to set the smoothness term in the energy function. After that, all pixels were assigned to binary labels by minimizing the energy function by dynamic graph cut algorithm. Finally, the proposed algorithm was verified on different videos. Experimental results prove that the proposed method can cut the foreground object accurately with real time ability.