基于领域知识的唇形跟踪

Swapna Agarwal, D. Mukherjee
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引用次数: 1

摘要

近年来,对鲁棒性面部特征跟踪尤其是唇形跟踪算法的需求急剧增加。我们实现了一个受人类感知启发的活动轮廓(蛇)模型,用于唇形跟踪。除了常规的张力、刚度(内部能量)和梯度大小(外部能量)的能量项外,我们建议在唇形约束和局部区域轮廓约束中加入来自领域知识的能量项。对能量泛函进行广义确定性退火(GDA)更新,使解摆脱了能量空间中的次优局部极小值,得到了更好的跟踪结果。实验结果表明,在基于梯度幅度和局部区域的跟踪方法均无法实现的情况下,该方法能够有效地适应唇边界高度变形的情况。我们已经做了许多实验来评估我们的方法与现有的最先进的方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lip tracking under varying expressions utilizing domain knowledge
In recent years the need of a robust facial component tracking especially lip tracking algorithm has increased dramatically. We implement an active contour (snake) model inspired by human perception for lip tracking. In addition to the conventional energy terms for tension, rigidity (internal energy) and gradient magnitude (external energy) we propose to include energy terms from domain knowledge for lip shape constraint and local region profile constraint. Generalized deterministic annealing (GDA) update of the energy functional helps the solution to escape suboptimal local minima in the energy space and give better tracking result. Experimental results show that the proposed method efficiently adapts to the highly deformable lip boundaries even for lips with indistinct edges and colored (adorned) lips where gradient magnitude based or local region based tracking methods respectively fail. We have done a number of experiments to evaluate the performance of our method in comparison with the existing state-of-the-art methods.
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