中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Flowing on Riemannian Manifold: Domain Adaptation by Shifting Covariance

文献类型:期刊论文

作者Cui, Zhen1,2; Li, Wen3; Xu, Dong3; Shan, Shiguang2; Chen, Xilin2; Li, Xuelong4
刊名ieee transactions on cybernetics
出版日期2014-12-01
卷号44期号:12页码:2264-2273
关键词Domain adaptation riemannian manifold support vector machine
ISSN号2168-2267
产权排序4
合作状况国内
英文摘要domain adaptation has shown promising results in computer vision applications. in this paper, we propose a new unsupervised domain adaptation method called domain adaptation by shifting covariance (dasc) for object recognition without requiring any labeled samples from the target domain. by characterizing samples from each domain as one covariance matrix, the source and target domain are represented into two distinct points residing on a riemannian manifold. along the geodesic constructed from the two points, we then interpolate some intermediate points (i.e., covariance matrices), which are used to bridge the two domains. by utilizing the principal components of each covariance matrix, samples from each domain are further projected into intermediate feature spaces, which finally leads to domain-invariant features after the concatenation of these features from intermediate points. in the multiple source domain adaptation task, we also need to effectively integrate different types of features between each pair of source and target domains. we additionally propose an svm based method to simultaneously learn the optimal target classifier as well as the optimal weights for different source domains. extensive experiments demonstrate the effectiveness of our method for both single source and multiple source domain adaptation tasks.
WOS标题词science & technology ; technology
类目[WOS]computer science, artificial intelligence ; computer science, cybernetics
研究领域[WOS]computer science
关键词[WOS]event recognition ; videos
收录类别SCI ; EI
语种英语
WOS记录号WOS:000345629000003
公开日期2015-03-19
源URL[http://ir.opt.ac.cn/handle/181661/22414]  
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.Huaqiao Univ, Coll Comp Sci & Technol, Xiamen 361021, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
3.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore
4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt Imagery Anal & Learning, Xian 710119, Peoples R China
推荐引用方式
GB/T 7714
Cui, Zhen,Li, Wen,Xu, Dong,et al. Flowing on Riemannian Manifold: Domain Adaptation by Shifting Covariance[J]. ieee transactions on cybernetics,2014,44(12):2264-2273.
APA Cui, Zhen,Li, Wen,Xu, Dong,Shan, Shiguang,Chen, Xilin,&Li, Xuelong.(2014).Flowing on Riemannian Manifold: Domain Adaptation by Shifting Covariance.ieee transactions on cybernetics,44(12),2264-2273.
MLA Cui, Zhen,et al."Flowing on Riemannian Manifold: Domain Adaptation by Shifting Covariance".ieee transactions on cybernetics 44.12(2014):2264-2273.

入库方式: OAI收割

来源:西安光学精密机械研究所

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