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Mouth shape detection and tracking using an active mesh

机译:使用活动网格进行嘴形检测和跟踪

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Abstract: In this paper, we describe an approach to detecting and tracking certain feature points in the mouth region in a talking head sequence. These feature points are interconnected in a polygononal mesh so that the detection and tracking of these points is based on the information not only at these points but also in the surrounding elements. The detection of the nodes in an initial frame is accomplished by a feature detection algorithm. The tracking of these nodes in successive frames is obtained by deforming the mesh so that, when one mesh is warped to the other, the image patterns over corresponding elements in two meshes match with each other. This is accomplished by a modified Newton algorithm which iteratively minimized the error between the two images after mesh-based- warping. The numerical calculation involved in the optimization approach is simplified by using the concept of master elements and shape functions in the finite element method. This algorithm has been applied to a SIF resolution sequence, which contains fairly rapid mouth movement. Our simulation results show that this algorithm can locate and track the feature points in the mouth region quite accurately.!8
机译:摘要:在本文中,我们描述了一种在说话的头部序列中检测和跟踪嘴巴区域中某些特征点的方法。这些特征点在多边形网格中互连,因此这些点的检测和跟踪不仅基于这些点的信息,而且还基于周围元素的信息。初始帧中节点的检测是通过特征检测算法完成的。这些节点在连续帧中的跟踪是通过使网格变形来实现的,这样,当一个网格扭曲到另一个网格时,两个网格中相应元素上的图像图案就会相互匹配。这是通过改进的牛顿算法完成的,该算法迭代地最小化了基于网格的变形后两个图像之间的误差。通过使用有限元方法中的主元素和形状函数的概念,简化了优化方法中涉及的数值计算。该算法已应用于包含相当快速的嘴巴移动的SIF解析序列。我们的仿真结果表明,该算法可以非常准确地定位和跟踪嘴巴区域中的特征点!! 8

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