UM  > 科技學院
Pairwise linear regression classification for image set retrieval
Feng Q.; Zhou Y.; Lan R.
2016
Conference Name2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Source PublicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2016-January
Pages4865-4872
Conference DateJUN 27-30, 2016
Conference PlaceSeattle, WA
Abstract

This paper proposes the pairwise linear regression classification (PLRC) for image set retrieval. In PLRC, we first define a new concept of the unrelated subspace and introduce two strategies to constitute the unrelated subspace. In order to increase the information of maximizing the query set and the unrelated image set, we introduce a combination metric for two new classifiers based on two constitution strategies of the unrelated subspace. Extensive experiments on six well-known databases prove that the performance of PLRC is better than that of DLRC and several state-of-theart classifiers for different vision recognition tasks: clusterbased face recognition, video-based face recognition, object recognition and action recognition.

DOIhttp;//doi.org/10.1109/CVPR.2016.526
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000400012304100
Fulltext Access
Citation statistics
Cited Times [WOS]:16   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Feng Q.,Zhou Y.,Lan R.. Pairwise linear regression classification for image set retrieval[C],2016:4865-4872.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Feng Q.]'s Articles
[Zhou Y.]'s Articles
[Lan R.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Feng Q.]'s Articles
[Zhou Y.]'s Articles
[Lan R.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Feng Q.]'s Articles
[Zhou Y.]'s Articles
[Lan R.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.