|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM262714272 |
| 003 |
DE-627 |
| 005 |
20231224202342.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231224s2016 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1109/TIP.2016.2592703
|2 doi
|
| 028 |
5 |
2 |
|a pubmed24n0875.xml
|
| 035 |
|
|
|a (DE-627)NLM262714272
|
| 035 |
|
|
|a (NLM)27448352
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Zhang, Liyan
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Query-Driven Approach to Face Clustering and Tagging
|
| 264 |
|
1 |
|c 2016
|
| 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 23.05.2017
|
| 500 |
|
|
|a Date Revised 23.05.2017
|
| 500 |
|
|
|a published: Print-Electronic
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a In the era of big data, a traditional offline setting to processing image data is simply not tenable. We simply do not have the computational power to process every image with every possible tag; moreover, we will not have the manpower to clean up the potentially noisy results. In this paper, we introduce a query-driven approach to visual tagging, focusing on the application of face tagging and clustering. We integrate active learning with query-driven probabilistic databases. Rather than asking a user to provide manual labels so as to minimize the uncertainty of labels (face tags) across the entire data set, we ask the user to provide labels that minimize the uncertainty of his/her query result (e.g., "How many times did Bob and Jim appear together?"). We use a data-driven Gaussian process model of facial appearance to write the probabilistic estimates of facial identity into a probabilistic database, which can then support inference through query answering. Importantly, the database is augmented with contextual constraints (faces in the same image cannot be the same identity, while faces in the same track must be identical). Experiments on the real-world photo collections demonstrate the effectiveness of the proposed method
|
| 650 |
|
4 |
|a Journal Article
|
| 700 |
1 |
|
|a Wang, Xikui
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Kalashnikov, Dmitri V
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Mehrotra, Sharad
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Ramanan, Deva
|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 25(2016), 10 vom: 02. Okt., Seite 4504-13
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
|
| 773 |
1 |
8 |
|g volume:25
|g year:2016
|g number:10
|g day:02
|g month:10
|g pages:4504-13
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TIP.2016.2592703
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 25
|j 2016
|e 10
|b 02
|c 10
|h 4504-13
|