[1]汪 璠,沈世斌,章 悦,等.基于HOG-SIFT融合优化的多人脸特征提取方法[J].南京师范大学学报(工程技术版),2020,20(03):043-49.[doi:10.3969/j.issn.1672-1292.2020.03.008]
　Wang Fan,Shen Shibin,Zhang Yue,et al.A Multi-Face Feature Extraction Method Based onHOG-SIFT Feature Fusion Optimization[J].Journal of Nanjing Normal University(Engineering and Technology),2020,20(03):043-49.[doi:10.3969/j.issn.1672-1292.2020.03.008]
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基于HOG-SIFT融合优化的多人脸特征提取方法
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
20卷
期数:
2020年03期
页码:
043-49
栏目:
计算机科学与技术
出版日期:
2020-09-15

文章信息/Info

Title:
A Multi-Face Feature Extraction Method Based onHOG-SIFT Feature Fusion Optimization
文章编号:
1672-1292(2020)03-0043-07
作者:
汪 璠1; 2; 沈世斌1; 3; 章 悦1; 2; 谢 非1; 2; 3; 陆 飞1; 2; 刘益剑1; 2; 3
(1.南京师范大学电气与自动化工程学院,江苏 南京 210023)(2.南京师范大学江苏省三维打印装备与制造重点实验室,江苏 南京 210023)(3.南京智能高端装备研究院,江苏 南京 210042)
Author(s):
Wang Fan1; 2; Shen Shibin1; 3; Zhang Yue1; 2; Xie Fei1; 2; 3; Lu Fei1; 2; Liu Yijian1; 2; 3
(1.School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210023,China)(2.Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing,Nanjing Normal University,Nanjing 210023,China)(3.Nanjing Industry Institute for Advanced Intelligent Equipment,Nanjing 210042,China)
关键词:
人脸识别; 特征提取; 多人脸特征; 复杂背景
Keywords:
face recognition; feature extraction; multi-face feature; complex background
分类号:
TP391.41
DOI:
10.3969/j.issn.1672-1292.2020.03.008
文献标志码:
A
摘要:
针对昏暗光线及复杂背景下人脸特征提取效果易受环境因素干扰影响的问题,在进行人脸图像预处理过程中引入双边滤波处理,进一步研究基于自商图像理论的人脸图像光照干扰抑制方法; 结合HOG特征较好的全局性以及SIFT特征对复杂背景影响较好的适应性,提出一种基于HOG-SIFT融合优化的多人脸特征提取方法. 试验结果表明,该方法可有效实现昏暗光线环境及复杂背景下多人脸特征提取功能.
Abstract:
Aiming at the problem that the effect of face feature extraction in dim light and complex backgrounds is easily affected by the interence of environmental factors,bilateral filter is firstly exploited in the process of face image preprocessing,and the illumination interference suppression method of face image based on self-quotient image theory is further studied. Secondly,a multi-face feature extraction method based on HOG-SIFT fusion optimization is proposed with the combination of the better globality of HOG features and the better adaptability of SIFT feature under complex background. Finally,the experimental results show that the proposed method can effectively extract multi-face features in dark light environment and complex background.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-05-31.
基金项目:国家自然科学基金项目(41974033、61601228)、江苏省自然科学基金项目(BK20180726、BK20161021)、江苏省高校自然科学基金项目(17KJB510031)、江苏省三维打印装备与制造重点实验室项目(BM2013006)资助开放课题(3DL201607).
通讯作者:沈世斌,高级实验师,研究方向:机器视觉与图像处理、智能车与嵌入式系统. E-mail:63018@njnu.edu.cn
更新日期/Last Update: 2020-09-15