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Fitting Multiple Connected Ellipses to an Image Silhouette Hierarchically

机译:将多个连接的椭圆分层拟合到图像轮廓

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摘要

In this paper, we seek to fit a model, specified in terms of connected ellipses, to an image silhouette. Some algorithms that have attempted this problem are sensitive to initial guesses and also may converge to a wrong solution when they attempt to minimize the objective function for the entire ellipse structure in one step. We present an algorithm that overcomes these issues. Our first step is to temporarily ignore the connections, and refine the initial guess using unconstrained Expectation-Maximization (EM) for mixture Gaussian densities. Then the ellipses are reconnected linearly. Lastly, we apply the Levenberg-Marquardt algorithm to fine-tune the ellipse shapes to best align with the contour. The fitting is achieved in a hierarchical manner based upon the joints of the model. Experiments show that our algorithm can robustly fit a complex ellipse structure to a corresponding shape for several applications.
机译:在本文中,我们试图将根据连接的椭圆指定的模型拟合到图像轮廓。某些尝试过此问题的算法对初始猜测很敏感,并且在尝试一步将整个椭圆结构的目标函数最小化时,也可能收敛于错误的解决方案。我们提出了一种克服这些问题的算法。我们的第一步是暂时忽略连接,并使用混合高斯密度的无约束期望最大化(EM)来优化初始猜测。然后将椭圆线性重新连接。最后,我们应用Levenberg-Marquardt算法微调椭圆形状,使其与轮廓最佳对齐。基于模型的关节以分层方式实现拟合。实验表明,我们的算法可以针对多种应用将复杂的椭圆结构稳固地拟合为相应的形状。

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