文献类型：期刊文献

中文题名：基于SOM网络的三维人脸表情识别

英文题名：3D facial expression recognition based on self organizing mapping network

作者：李淑红[1];尹小娟[1];句全[1]

第一作者：李淑红

机构：[1]河南财经政法大学计算机与信息工程学院

第一机构：河南财经政法大学计算机与信息工程学院

年份：2013

卷号：28

期号：5

起止页码：70-73

中文期刊名：郑州轻工业学院学报：自然科学版

收录：CSTPCD

语种：中文

中文关键词：三维人脸表情识别;形状描述;自组织神经网络

外文关键词：3D facial expression recognition; shape description; self organizing mapping（SOM） network

摘要：针对二维人脸表情数据所含信息量有限,在光照、姿态变化的情况下识别性能较差等缺点,提出了基于SOM网络的三维人脸表情识别方法.该方法用均值和方差来描述人脸表面的凸凹情况,以此作为进一步描述人脸表情变化的特征数据.仿真实验结果表明,采用SOM网络的分类效果和识别效果,均优于AdaBoost算法.
It is well known that the two-dimensional facial expression data contains limited information,and the poor performance of the facial expression recognition under the condition of changing illumination and posture. In order to overcome these shortcomings of the 2D facial expression,In this paper,we propose and explore a novel method to recognize human facial expression in 3D based on Self Organizing Map（ SOM）.In the method,the mean and variance are used to describe the convex and concave surface of the face which become the facial expression change characteristics datas. The simulation experimental results showed that the effect of using the classification and recognition of SOM network was superior to the AdaBoost algorithm.