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引用次数: 29

摘要

本文提出了一种基于图割的运动目标检测系统。我们的方法依赖于使用光流算法和基于混合高斯的经典背景减去模块的运动建模。我们的方法的主要贡献是两个掩模模型的融合,以及图切算法使用的特定成本函数。在CDnet 2014基准上进行的实验表明,我们的系统在恶劣天气或PTZ等场景下具有非常好的效果,但在检测场景中的微小变化时鲁棒性较差。
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Change detection based on graph cuts
In this paper we propose a moving object detection system based on Graph Cut. Our method relies on motion modelling using an optical flow algorithm and a classical background subtraction module based on Mixture of Gaussians. The main contribution in our approach is the fusion of the two mask models, as well as the particular cost function used by the Graph Cut algorithm. The experiments as performed on CDnet 2014 benchmark showed that our system has very good results in scenarios such as Bad Weather or PTZ, but is less robust in detecting small changes in the scene.
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