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A Novel Genetic Algorithm for 3D Facial Landmark Localization

机译:一种新型遗传算法3D面部地标定位

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This paper introduces Evolutionary Putsuit(EP) as a novel approach for 3D facial landmark localization. Leveraging the global optimization ability of Genetic Algorithm(GA), an innovative framework for detecting local features, like nose tips and eye-corners, on 3D face data is proposed. Facial landmarks are localized by combining responses of several weak classifiers as basic building blocks. A genetic algorithm is employed for searching the optimal way to combine these building blocks, in order to construct a classifier with high detection accuracy. This GA-based facial landmark detection method is evaluated on the FRGC v1 database; it shows promising results that the GA searching process is able to produce an effective feature classifier from a relatively small training set, achieving a strong landmark localization ability.
机译:本文介绍了进化的Putsuit(EP)作为3D面部地标定位的新方法。提出了一种遗传算法(GA)的全局优化能力,提出了一种创新框架,用于检测局部特征,如鼻尖和眼角,在3D面部数据上。面部地标通过将几个弱分类器的响应与基本构建块相结合而定。采用遗传算法来搜索结合这些构建块的最佳方式,以便构造具有高检测精度的分类器。该基于GA的面部地标检测方法在FRGC V1数据库上进行评估;它显示了GA搜索过程能够从相对小的训练集生产有效的特征分类器,实现强大的地标定位能力。

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