Mutual Component Analysis for Heterogeneous Face Recognition

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Mutual Component Analysis for Heterogeneous Face Recognition
	Li, Zhifeng 1; Gong, Dihong 1; Li, Qiang 2; Tao, Dacheng2 ; Li, Xuelong3
刊名	acm transactions on intelligent systems and technology
	2016-04-01
卷号	7 期号:3
关键词	Algorithms Performance Face recognition heterogeneous face recognition mutual component analysis (MCA)
ISSN号	2157-6904
产权排序	3
英文摘要	heterogeneous face recognition, also known as cross-modality face recognition or intermodality face recognition, refers to matching two face images from alternative image modalities. since face images from different image modalities of the same person are associated with the same face object, there should be mutual components that reflect those intrinsic face characteristics that are invariant to the image modalities. motivated by this rationality, we propose a novel approach called mutual component analysis (mca) to infer the mutual components for robust heterogeneous face recognition. in the mca approach, a generative model is first proposed to model the process of generating face images in different modalities, and then an expectation maximization (em) algorithm is designed to iteratively learn the model parameters. the learned generative model is able to infer the mutual components (which we call the hidden factor, where hidden means the factor is unreachable and invisible, and can only be inferred from observations) that are associated with the person's identity, thus enabling fast and effective matching for cross-modality face recognition. to enhance recognition performance, we propose an mca-based multiclassifier framework using multiple local features. experimental results show that our new approach significantly outperforms the state-of-the-art results on two typical application scenarios: sketch-to-photo and infrared-to-visible face recognition.
学科主题	计算机应用其他学科（含图像处理）
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence ; computer science, information systems
研究领域[WOS]	computer science
关键词[WOS]	discriminant-analysis ; spectral regression ; sketch recognition ; classification ; performance ; framework
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000373911200003
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/27880]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing 100864, Peoples R China 2.Univ Technol Sydney, Fac Engn & Informat Technol, Ctr Quantum Computat & Intelligent Syst, 81 Broadway, Ultimo, NSW 2007, Australia 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Li, Zhifeng,Gong, Dihong,Li, Qiang,et al. Mutual Component Analysis for Heterogeneous Face Recognition[J]. acm transactions on intelligent systems and technology,2016,7(3).
APA	Li, Zhifeng,Gong, Dihong,Li, Qiang,Tao, Dacheng,&Li, Xuelong.(2016).Mutual Component Analysis for Heterogeneous Face Recognition.acm transactions on intelligent systems and technology,7(3).
MLA	Li, Zhifeng,et al."Mutual Component Analysis for Heterogeneous Face Recognition".acm transactions on intelligent systems and technology 7.3(2016).