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论文类型：期刊论文

发表时间：2016-11-01

发表刊物：PATTERN RECOGNITION LETTERS

收录刊物：SCIE、EI、Scopus

卷号：83

页面范围：395-402

ISSN号：0167-8655

关键字：3D facial landmark detection; Conformal mapping; 2D texture regression

摘要：3D facial alignment typically requires the accurate estimate of facial landmarks. Most existing landmark detection methods use geometry characterization or resort to regression algorithms performed on point clouds or range images. A method combining both 3D geometry information and 2D texture has rarely been investigated. In this paper, we propose a novel 3D facial landmark localization algorithm, based on conformal geometric mapping, that can convert a 3D model to 2D using both geometry and texture information. Then a two-layers-regression method is used to improve the stability of landmark localization on the 2D geometry images. This method is impervious to pose changes and robust with respect to changes in expression. We evaluated the proposed approach on publicly available datasets and demonstrate how the use of 2D regression methods boosts the robustness and accuracy of 3D facial landmark localization. (C) 2016 Elsevier B.V. All rights reserved.