Feature detection and tracking on geometric mesh data using a combined global and local shape model for face analysis

Shaun J. Canavan, L. Yin
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引用次数: 5

Abstract

Automatic geometric feature localization is the first step towards the 3D based face analysis. In this paper we propose a shape model with a local and global constraint for feature detection. Such a so-called shape-index based statistical shape model (SI-SSM) makes use of the global shape of the facial data as well as local patches, consisting of shape index values, around landmark features. The fitting process and the performance of our proposed method are evaluated in terms of various imaging conditions and data qualities. The efficacy of the detected landmarks is validated through applications for geometric based face identification.
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基于全局与局部相结合的几何网格数据特征检测与跟踪
自动几何特征定位是实现三维人脸分析的第一步。本文提出了一种具有局部约束和全局约束的形状模型用于特征检测。这种所谓的基于形状指数的统计形状模型(SI-SSM)利用了面部数据的全局形状以及由形状指标值组成的局部斑块,这些斑块围绕着地标特征。根据不同的成像条件和数据质量对拟合过程和我们提出的方法的性能进行了评估。通过基于几何的人脸识别应用验证了检测到的地标的有效性。
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