基于SIFT算法的多表情人脸识别

刘洋; 韩广良; 史春蕾

doi:10.3788/YJYXS20163112.1156

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基于SIFT算法的多表情人脸识别

显示与图像 | 更新时间：2020-07-07

- 基于SIFT算法的多表情人脸识别
- Recognition of expression-variant faces based on SIFT method
- 液晶与显示 2016年31卷第12期页码：1156-1160
- 作者机构：
  
  1.长春师范大学物理学院, 吉林长春 130032
  2.中国科学院长春光学精密机械与物理研究所图像处理技术研究部, 吉林长春 130033
- 作者简介：
  
  刘洋(1994-), 女, 吉林长春人, 主要从事图像处理方面的研究。E-mail:178388617@qq.com
- 基金信息：
  
  吉林省教育厅“十二五”科学技术研究项目(2015359);长春师范大学实验教学改革研究项目;Supported by "Twelfth Five-Year" Science and Technology Research Project of the Education Department of Jilin Province(2015359);Experiment teaching reformation research project of Changchun Normal University
- DOI：10.3788/YJYXS20163112.1156
  中图分类号： TP391.4
- 收稿日期：2016-11-07，
  
  录用日期：2016-12-6，
  
  纸质出版日期：2016-12-05
- 稿件说明：
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刘洋, 韩广良, 史春蕾. 基于SIFT算法的多表情人脸识别[J]. 液晶与显示, 2016,31(12):1156-1160.

Yang LIU, Guang-liang HAN, Chun-lei SHI. Recognition of expression-variant faces based on SIFT method[J]. Chinese journal of liquid crystals and displays, 2016, 31(12): 1156-1160.
刘洋, 韩广良, 史春蕾. 基于SIFT算法的多表情人脸识别[J]. 液晶与显示, 2016,31(12):1156-1160. DOI： 10.3788/YJYXS20163112.1156.

Yang LIU, Guang-liang HAN, Chun-lei SHI. Recognition of expression-variant faces based on SIFT method[J]. Chinese journal of liquid crystals and displays, 2016, 31(12): 1156-1160. DOI： 10.3788/YJYXS20163112.1156.

摘要

目前人脸识别系统在识别表情变化的人脸图像时识别准确率会降低，多表情人脸识别在人脸识别领域仍是一个热门的研究方向。本文采用SIFT算法对多表情人脸进行识别，在多表情人脸库上进行了两类仿真实验：实验一中对比了同一个人的不同表情的识别效果，实验二中对比了两个不同的人的相同表情的识别效果，实验结果表明SIFT算法能够克服不同人脸间的整体相似性并能有效提取出人脸的局部细节特征。对Jaffe表情库进行仿真实验，取得了当阈值

=0.35时对多表情人脸图像的正确识别率95.69%，实验结果表明，将SIFT算法应用于多表情人脸识别有巨大的潜在科研价值。

Abstract

Prior research has shown that the performance of face recognition systems in variant expression condition degrades seriously compared with invariant expression condition. Face recognition with variant expression is a challenging problem. In this paper

SIFT method is proposed to research on face recognition with variant expression. Two experiments using SIFT method are performed on a variant expression face database. In experiment 1

two images of one person with different expression are compared. In experiment 2

two images of different persons with the same expression are compared. Experimental results show that SIFT method could overcome the whole comparability of different faces and extract the local detail features of face. Recognizing the variant expression face images in Jaffe library

we get the right recognition rate of 95.59% when threshold equals 0.35

the experiment demonstrates the huge potential of SIFT method in application to face recognition with variant expression.

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references

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