计算机工程与应用2019，Vol.55Issue(7)：40-47,8.DOI:10.3778/j.issn.1002-8331.1901-0216
基于多状态分层模型的有表情人脸配准
Face Alignment Across Expression Based on Multi State Layered Model
摘要
Abstract
The range of expression variety is discretized to be multi-state component model, which is used to describe nonlinear variety of a face. The hierarchical face alignment is achieved based on the cascade convolutional neural networks by introducing multi direction local gradient information and constructing the corresponding backprojection probability map to improve appearance representation of traditional grey images. The face shape initialization is realized and the current component state is predicted, according to the whole face and different regions. The face shape parameters are regressed to achieve final fine alignment, according to the chosen face model under correct state. The experiments performed on database demonstrate that the proposed method improves the robustness of face alignment under exaggerated expressions and correct rate, and convergence rate are increased under the considerable computational complexity.关键词
反投影概率图/多状态部件模型/卷积神经网络/形状参数更新/分层人脸配准Key words
backprojection probability map/multi-state component model/Convolutional Neural Network/shape param-eters update/hierarchical face alignment分类
交通工程引用本文复制引用
高宁,王兴元,王秀坤..基于多状态分层模型的有表情人脸配准[J].计算机工程与应用,2019,55(7):40-47,8.基金项目
国家自然科学基金(No.61603103,No.61673125) （No.61603103,No.61673125）
广东省自然科学基金(No.2016A030310293) （No.2016A030310293）
广州市科技计划科学研究专项(No.201707010013) （No.201707010013）
佛山科学技术学院研究生自由探索基金(No.2018LGZ02). （No.2018LGZ02）
