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A new deformable mesh model for face tracking using edge based features and novel sets of energy functions

机译:使用基于边缘的特征和新的能量函数集的用于面部跟踪的新的可变形网格模型

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摘要

This paper presents a new method for automatic human face locating and tracking. The proposed method consists of two modules including face locating and face tracking. The face locating module has a hierarchical structure, which consists of a skin color classifier together with AdaBoost based face detectors. The face tracking module is considered to be the main contribution of the paper. The module is based on the unstructured 2-D triangular deformable meshes, which employs a new robust and illumination insensitive feature extraction and matching algorithms as well as new sets of mesh energy functions. The feature extraction and matching algorithms are established upon edge points and their representation using fuzzy set theory, which is called fuzzy edges. For matching features, a multiresolution algorithm is utilized based on fuzzy edges and edge pyramid. The new mesh energy functions are also employed to manage both rigid and non-rigid motions in the head and face. Experimental results demonstrate the accuracy and stability of the proposed method for both face locating and face tracking.
机译:本文提出了一种新的人脸自动定位和跟踪方法。该方法由人脸定位和人脸跟踪两个模块组成。面部定位模块具有分层结构,该结构由肤色分类器和基于AdaBoost的面部检测器组成。人脸跟踪模块被认为是本文的主要贡献。该模块基于非结构化二维三角形可变形网格,该网格采用了新的鲁棒性和光照不敏感特征提取和匹配算法以及新的网格能量函数集。利用模糊集理论在边缘点及其表示上建立特征提取和匹配算法,称为模糊边缘。对于匹配特征,基于模糊边缘和边缘金字塔的多分辨率算法被使用。新的网格能量功能还用于管理头部和面部的刚性和非刚性运动。实验结果证明了该方法在人脸定位和人脸跟踪中的准确性和稳定性。

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