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Statistics of Flow Vectors and Its Application to the Voting Method for the Detection of Flow Fields

机译:流向量的统计及其在流场检测投票方法中的应用

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In this paper, we show that the randomized sampling and voting process detects linear flow filed as a model-fitting problem. We introduce a random sampling method for solving the least-square model-fitting-problem using a mathematical property for the construction of pseudo-inverse. If we use an appropriate number of images from a sequence of images, it is possible to detect subpixel motion in this sequence. We use the accumulator space for the unification of these flow vectors which are computed from different time intervals. Numerical examples for the test image sequences show the performance of our method.
机译:在本文中,我们表明随机抽样和投票过程将线性流场检测为模型拟合问题。我们介绍了一种随机抽样方法,可使用数学属性构造最小逆模型来解决最小二乘模型拟合问题。如果我们从图像序列中使用适当数量的图像,则可以检测此序列中的子像素运动。我们使用累加器空间来统一这些由不同时间间隔计算出的流向量。测试图像序列的数值示例说明了我们方法的性能。

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