|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM218954093 |
| 003 |
DE-627 |
| 005 |
20231224041736.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231224s2012 xx |||||o 00| ||eng c |
| 028 |
5 |
2 |
|a pubmed24n0730.xml
|
| 035 |
|
|
|a (DE-627)NLM218954093
|
| 035 |
|
|
|a (NLM)22736645
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Yuan, Xiao-Tong
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Visual classification with multitask joint sparse representation
|
| 264 |
|
1 |
|c 2012
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Completed 11.02.2013
|
| 500 |
|
|
|a Date Revised 21.09.2012
|
| 500 |
|
|
|a published: Print-Electronic
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a We address the problem of visual classification with multiple features and/or multiple instances. Motivated by the recent success of multitask joint covariate selection, we formulate this problem as a multitask joint sparse representation model to combine the strength of multiple features and/or instances for recognition. A joint sparsity-inducing norm is utilized to enforce class-level joint sparsity patterns among the multiple representation vectors. The proposed model can be efficiently optimized by a proximal gradient method. Furthermore, we extend our method to the setup where features are described in kernel matrices. We then investigate into two applications of our method to visual classification: 1) fusing multiple kernel features for object categorization and 2) robust face recognition in video with an ensemble of query images. Extensive experiments on challenging real-world data sets demonstrate that the proposed method is competitive to the state-of-the-art methods in respective applications
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Research Support, Non-U.S. Gov't
|
| 700 |
1 |
|
|a Liu, Xiaobai
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Yan, Shuicheng
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 21(2012), 10 vom: 02. Okt., Seite 4349-60
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
|
| 773 |
1 |
8 |
|g volume:21
|g year:2012
|g number:10
|g day:02
|g month:10
|g pages:4349-60
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 21
|j 2012
|e 10
|b 02
|c 10
|h 4349-60
|