Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition
Ren, Chuan-Xian1; Lei, Zhen2,3; Dai, Dao-Qing1; Li, Stan Z.2,3
2016-11-01
发表期刊IEEE TRANSACTIONS ON CYBERNETICS
卷号46期号:11页码:2656-2669
文章类型Article
摘要Robust descriptor-based subspace learning with complex data is an active topic in pattern analysis and machine intelligence. A few researches concentrate the optimal design on feature representation and metric learning. However, traditionally used features of single-type, e.g., image gradient orientations (IGOs), are deficient to characterize the complete variations in robust and discriminant subspace learning. Meanwhile, discontinuity in edge alignment and feature match are not been carefully treated in the literature. In this paper, local order constrained IGOs are exploited to generate robust features. As the difference-based filters explicitly consider the local contrasts within neighboring pixel points, the proposed features enhance the local textures and the order-based coding ability, thus discover intrinsic structure of facial images further. The multimodal features are automatically fused in the most discriminant subspace. The utilization of adaptive interaction function suppresses outliers in each dimension for robust similarity measurement and discriminant analysis. The sparsity-driven regression model is modified to adapt the classification issue of the compact feature representation. Extensive experiments are conducted by using some benchmark face data sets, e.g., of controlled and uncontrolled environments, to evaluate our new algorithm.
关键词Discontinuity Image Gradient Order Features Sparse Representation Subspace Learning
WOS标题词Science & Technology ; Technology
DOI10.1109/TCYB.2015.2484356
关键词[WOS]DIMENSIONALITY REDUCTION ; SPARSE REPRESENTATION ; VERIFICATION ; REGULARIZATION ; CLASSIFIER ; EIGENFACES ; DESCRIPTOR ; PATTERNS ; MODELS ; POSE
收录类别SCI
语种英语
项目资助者National Science Foundation of China(11171354 ; Ministry of Education of China(SRFDP-20120171120007 ; Natural Science Foundation of Guangdong Province(S2013020012796) ; Fundamental Research Funds for the Central Universities(13lgpy26) ; Open Project Program of the National Laboratory of Pattern Recognition ; 61203248 ; 20120171110016) ; 61375033 ; 61572536)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号WOS:000386227000023
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13329
专题模式识别国家重点实验室_生物识别与安全技术研究
作者单位1.Sun Yat Sen Univ, Sch Math & Computat Sci, Intelligent Data Ctr, Guangzhou 510275, Guangdong, Peoples R China
2.Chinese Acad Sci, Ctr Biometr & Secur Res, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Ren, Chuan-Xian,Lei, Zhen,Dai, Dao-Qing,et al. Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition[J]. IEEE TRANSACTIONS ON CYBERNETICS,2016,46(11):2656-2669.
APA Ren, Chuan-Xian,Lei, Zhen,Dai, Dao-Qing,&Li, Stan Z..(2016).Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition.IEEE TRANSACTIONS ON CYBERNETICS,46(11),2656-2669.
MLA Ren, Chuan-Xian,et al."Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition".IEEE TRANSACTIONS ON CYBERNETICS 46.11(2016):2656-2669.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
ChuanxianRen-ELGOF-T(1998KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Ren, Chuan-Xian]的文章
[Lei, Zhen]的文章
[Dai, Dao-Qing]的文章
百度学术
百度学术中相似的文章
[Ren, Chuan-Xian]的文章
[Lei, Zhen]的文章
[Dai, Dao-Qing]的文章
必应学术
必应学术中相似的文章
[Ren, Chuan-Xian]的文章
[Lei, Zhen]的文章
[Dai, Dao-Qing]的文章
相关权益政策
暂无数据
收藏/分享
文件名: ChuanxianRen-ELGOF-TCYB.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。