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Landmark Fitting for Sequential Faces Based on Active Shape Model and Tracking Correction

机译:基于主动形状模型和跟踪校正的序贯面的地标拟合

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In this paper, a method of landmark fitting for sequential faces is presented based on active shape model(ASM) and tracking correction. This method overcomes the loss of consecutive information between frames, and makes full use of the motion variation information of video sequences in time and space dimensions. Firstly, the optical flow values of several key points on the face are calculated by the large displacement optical flow model. Secondly, the positions of these points in the current frame are located to modify the global shape model of ASM and conduct the precise localization of landmarks in landmark searching. Finally, the rationality of landmark is suppressed to obtain the ultimate results. Our proposed method observably improves the accurate localization of ASM for deformed faces, and takes full advantage of the continuity among video sequences, so that it has significant effect on landmark fitting for sequential faces. Compared with ASM, extensive experiments show that our method performs outstandingly in terms of accuracy and robustness.
机译:本文基于主动形状模型(ASM)和跟踪校正来呈现用于顺序面的地标拟合方法。该方法克服了帧之间的连续信息的丢失,并充分利用时间和空间尺寸的视频序列的运动变化信息。首先,面对若干键点的光学流量由大的位移光学流模型计算。其次,当前帧中的这些点的位置所在以修改ASM的全局形状模型,并进行地标搜索中地标的精确定位。最后,抑制了地标的合理性以获得最终结果。我们提出的方法可观察地提高了ASM的为变形面的精确定位,以及将视频序列中的连续性的充分利用,使之具有对界标用于顺序面嵌合显著效果。与ASM相比,广泛的实验表明,我们的方法在准确性和鲁棒性方面表现出突出的。

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