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在线高斯混合模型和纹理支持的运动分割

Motion Segmentation via On-line Gaussian Mixture Model and Texture

  • 摘要: 运动分割是基于视频的运动分析中的基本问题.通过颜色和纹理特征的线性组合,实现了一种新的检测运动目标的算法.在线高斯混合模型不仅用于对背景进行更新,而且也用于计算像素颜色差异和颜色权值;纹理特征用于描述局部区域内的结构信息,提高了运动检测算法的鲁棒性.对不同场景的运动分割结果表明,该算法是高效和实用的.

     

    Abstract: Motion segmentation is a fundamental problem in video-based motion analysis. This paper implements a new method to detect moving objects, based on the linear fusion of color and texture features. The on-line Gaussian mixture model is employed to update the background image, and to calculate for every pixel the color difference and its corresponding color weight. Texture information is used on the other hand to describe the local structure information of pixel neighbor so as to enhance the robustness of motion segmentation. The experimental results of different real scenes show that the proposed method is effective and practical.

     

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