Agbolade Olalekan, Nazri Azree, Yaakob Razali, Ghani Abdul Azim Abd, Cheah Yoke Kqueen
Department of Computer Science, Faculty of Computer Science & IT, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Department of Software Engineering, Faculty of Computer Science & IT, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
PeerJ Comput Sci. 2020 Jan 16;6:e249. doi: 10.7717/peerj-cs.249. eCollection 2020.
Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks. This paper proposes a homologous multi-point warping for 3D facial landmarking, which is verified experimentally on each of the target objects in a given dataset using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks). This is achieved by building a template mesh as a reference object and applying this template to each of the targets in three datasets using an artificial deformation approach. The semi-landmarks are subjected to sliding along tangents to the curves or surfaces until the bending energy between a template and a target form is minimal. The results indicate that our method can be used to investigate shape variation for multiple datasets when implemented on three databases (Stirling, FRGC and Bosphorus).
多年来，神经科学家和心理物理学家一直在探讨面部分析的数据采集应该整体进行还是采用局部特征分析。这导致了各种先进的人脸识别方法被提出，尤其是使用面部标志点的技术。当前的三维面部标志点方法涉及一个数学上复杂且耗时的工作流程，包括半标志点滑动任务。本文提出了一种用于三维面部标志点定位的同源多点变形方法，该方法在给定数据集中的每个目标对象上使用500个标志点（16个解剖学固定点和484个滑动半标志点）进行了实验验证。这是通过构建一个模板网格作为参考对象，并使用人工变形方法将该模板应用于三个数据集中的每个目标来实现的。半标志点沿着曲线或表面的切线滑动，直到模板和目标形状之间的弯曲能量最小。结果表明，当在三个数据库（斯特林、FRGC和博斯普鲁斯）上实施时，我们的方法可用于研究多个数据集的形状变化。
