一种新的运动检测及轮廓追踪方法

A Novel Statistical Model for Motion Detection and Contour Tracing

  • 摘要: 构建了基于块区域二阶矩比的三帧差分运动检测模型,应用文献1中的核密度估计模型来滤除其中的非运动区域,并采用支持向量聚类实现多目标检测。给出了运动物体轮廓快速追踪的RW算法,该算法不必考虑检测区域内部的细节问题,能够充分利用所检测到的边缘信息,比较符合人眼对轮廓的搜索习惯。最后给出了实验结果。

     

    Abstract: In the first section, according to the assumption that only the silhouette could be extracted to describe the motion of a moving object, a three-frame differencing model is constructed based on the variance ratio of successive blocks of different frames, simultaneously the Gaussian kernel based density estimation model in \ is used as a filter to suppress false positives, and the SVC algorithm in \ is also employed to realize real-time multi-object motion detection. A novel contour tracing algorithm, namely the RW (roller wheel) method, is proposed in the next section. Edge information detected by the forgoing model can be fully used by this algorithm, while the interior details will be skipped. This algorithm works in a similar way that human vision system works. Experimental results are given in the end.

     

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