Describable Visual Attributes for Face Verification and Image Search

We introduce the use of describable visual attributes for face verification and image search. Describable visual attributes are labels that can be given to an image to describe its appearance. This paper focuses on images of faces and the attributes used to describe them, although the concepts also...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 33(2011), 10 vom: 01. Okt., Seite 1962-77
1. Verfasser: Kumar, Neeraj (VerfasserIn)
Weitere Verfasser: Berg, Alexander C, Belhumeur, Peter N, Nayar, Shree K
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2011
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S.
LEADER 01000naa a22002652 4500
001 NLM206440022
003 DE-627
005 20231223235927.0
007 cr uuu---uuuuu
008 231223s2011 xx |||||o 00| ||eng c
024 7 |a 10.1109/TPAMI.2011.48  |2 doi 
028 5 2 |a pubmed24n0688.xml 
035 |a (DE-627)NLM206440022 
035 |a (NLM)21383395 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Kumar, Neeraj  |e verfasserin  |4 aut 
245 1 0 |a Describable Visual Attributes for Face Verification and Image Search 
264 1 |c 2011 
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 11.03.2016 
500 |a Date Revised 01.03.2022 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a We introduce the use of describable visual attributes for face verification and image search. Describable visual attributes are labels that can be given to an image to describe its appearance. This paper focuses on images of faces and the attributes used to describe them, although the concepts also apply to other domains. Examples of face attributes include gender, age, jaw shape, nose size, etc. The advantages of an attribute-based representation for vision tasks are manifold: They can be composed to create descriptions at various levels of specificity; they are generalizable, as they can be learned once and then applied to recognize new objects or categories without any further training; and they are efficient, possibly requiring exponentially fewer attributes (and training data) than explicitly naming each category. We show how one can create and label large data sets of real-world images to train classifiers which measure the presence, absence, or degree to which an attribute is expressed in images. These classifiers can then automatically label new images. We demonstrate the current effectiveness--and explore the future potential--of using attributes for face verification and image search via human and computational experiments. Finally, we introduce two new face data sets, named FaceTracer and PubFig, with labeled attributes and identities, respectively 
650 4 |a Journal Article 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
700 1 |a Berg, Alexander C  |e verfasserin  |4 aut 
700 1 |a Belhumeur, Peter N  |e verfasserin  |4 aut 
700 1 |a Nayar, Shree K  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 33(2011), 10 vom: 01. Okt., Seite 1962-77  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:33  |g year:2011  |g number:10  |g day:01  |g month:10  |g pages:1962-77 
856 4 0 |u http://dx.doi.org/10.1109/TPAMI.2011.48  |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 33  |j 2011  |e 10  |b 01  |c 10  |h 1962-77