[1]杜吉祥,翟传敏,叶永青.使用稀疏约束非负矩阵分解算法的跨年龄人脸识别[J].智能系统学报,2012,7(3):271-277.
DU Jixiang,ZHAI Chuanmin,YE Yongqing.An agespan face recognition method based on an NMF algorithm with sparseness constraints[J].CAAI Transactions on Intelligent Systems,2012,7(3):271-277.
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DU Jixiang,ZHAI Chuanmin,YE Yongqing.An agespan face recognition method based on an NMF algorithm with sparseness constraints[J].CAAI Transactions on Intelligent Systems,2012,7(3):271-277.
使用稀疏约束非负矩阵分解算法的跨年龄人脸识别
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
7
期数:
2012年第3期
页码:
271-277
栏目:
学术论文—智能系统
出版日期:
2012-06-25
- Title:
- An agespan face recognition method based on an NMF algorithm with sparseness constraints
- 文章编号:
- 1673-4785(2012)03-0271-07
- Keywords:
- face recognition; agespan face recognition; nonnegative matrix factorization algorithm; sparseness constraints; facial aging simulation; virtual samples
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 人脸识别技术中除光线、姿态、表情因素外，由于年龄变化而导致的人脸形状和纹理上的变化会极大程度地影响人脸识别系统性能.对此，提出了一种使用稀疏非负矩阵分解算法来实现人脸老化模拟，然后将此方法应用于具有年龄跨度的人脸识别上，通过模拟虚拟样本来增强识别效果.实验结果表明，年龄跨度对人脸识别的确有较大的影响；当系数矩阵保持稀疏时，非负矩阵分解算法具有更强的特征提取能力；经过老化模拟增加虚拟样本后，其纹理老化效果明显地提高了跨年龄段的人脸识别的性能.
- Abstract:
- For face recognition technology, apart from lighting, gesture, and expression factors, variations in shape and texture of human faces due to aging factors also significantly affect the performance of face recognition systems. Using a sparseconstrained nonnegative matrix factorization (NMF) algorithm, a facial aging simulation method based on an improved prototype was first proposed and then applied to agespan face recognition to add virtual samples and heighten the recognition rate. Experimental results show that the age span indeed has a great effect on face recognition; the NMF algorithm has stronger feature extraction ability when the coefficient matrix is sparsely constrained. Furthermore, the recognition ratio is apparently improved after adding additional virtual samples by aging simulation of face texture features.
- 参考文献/References:
-
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备注/Memo
收稿日期：2011-12-08.网络出版日期：2012-05-27.
基金项目：国家自然科学基金资助项目(61175121)； 福建省自然科学基金资助项目(2011J01349)； 福建省教育厅科技计划资助项目(JA11004)； 华侨大学侨办科研基金资助项目(11QZR05)； 华侨大学基本科研业务费专项基金资助项目(JB-SJ1003).
通信作者：杜吉祥. E-mail: jxdu@hqu.edu.cn.
作者简介：杜吉祥，男，1977年生，副教授，工学博士，福建省计算机学会理事，主要研究方向为模式识别、智能计算、数字图像处理等.主持国家自然科学基金、福建省自然科学基金、中国科学院知识创新工程重要方向项目子课题、中国博士后科学基金特别资助项目等科研项目10余项.曾获2010年安徽省科学技术一等奖。发表学术论文40余篇.
翟传敏，女，1977年生，讲师，主要研究方向为模式识别、数字图像处理、计算机辅助设计等.
叶永青，男，1986年生，硕士研究生，主要研究方向为模式识别、数字图像处理等.
更新日期/Last Update:
2012-09-05