文献类型：会议论文

英文题名：Accumulating weighted segmentation in 3D face recognition

作者：Ju, Quan[1]; Hu, Haitao[1]; Wang, Yingfeng[1]

第一作者：Ju, Quan

机构：[1] School of Computer and Information Engineering, Henan University of Economics and Law, Henan Province, Zhengzhou, China

第一机构：河南财经政法大学计算机与信息工程学院

语种：英文

外文关键词：accumulating weight; expression variation; face recognition in 3D; face segmentation

摘要：In this paper, an accumulating weighted face segmentation approach based on the rigid level of human facial areas is introduced. A mass of 3D face data is measured and analysed to define the most expression-invariant region. Different locations or regions on the human face are observed to have dissimilar invariant levels. Thus, an accumulating weight method is proposed to represent the rigid degree under expression variations. In face identification experiments, performance by employing the accumulating weight is demonstrated to be higher than methods using the expression-invariant region and the full face, respectively. This accumulating weighted face segmentation approach outperforms other state-of-the-art methods in 3D face recognition experiments. ? 2022 Inderscience Enterprises Ltd.. All rights reserved.