The large success of online social platforms for creation, sharing and tagging of user-generated media has lead to a strong interest by the multimedia and computer vision communities in research on methods and techniques for annotating and searching social media. Visual content similarity, geo-tags and tag co-occurrence, together with social connections and comments, can be exploited to perform tag suggestion as well as to per-form content classification and c lustering and enable more effective semantic indexing and retrieval of visual data. However there is need to overcome the relatively low quality of these metadata: user produced tags and annotations are known to be ambiguous, imprecise and/or incomplete, excessively personalized and limited - and at the same time take into account the ‘web-scale’ quantity of media and the fact that social network users continuously add new images and create new terms. We will review the state of the art approaches to automatic annotation and tag refinement for social images, considering also the temporal patterns of their usage, and discuss extensions to tag suggestion and localization in web video sequences.

Data-driven approaches for social image and video tagging / Lamberto Ballan; Marco Bertini; Tiberio Uricchio; Alberto Del Bimbo. - In: MULTIMEDIA TOOLS AND APPLICATIONS. - ISSN 1380-7501. - STAMPA. - 74:(2015), pp. 1443-1468. [10.1007/s11042-014-1976-4]

Data-driven approaches for social image and video tagging

BALLAN, LAMBERTO;BERTINI, MARCO;URICCHIO, TIBERIO;DEL BIMBO, ALBERTO
2015

Abstract

The large success of online social platforms for creation, sharing and tagging of user-generated media has lead to a strong interest by the multimedia and computer vision communities in research on methods and techniques for annotating and searching social media. Visual content similarity, geo-tags and tag co-occurrence, together with social connections and comments, can be exploited to perform tag suggestion as well as to per-form content classification and c lustering and enable more effective semantic indexing and retrieval of visual data. However there is need to overcome the relatively low quality of these metadata: user produced tags and annotations are known to be ambiguous, imprecise and/or incomplete, excessively personalized and limited - and at the same time take into account the ‘web-scale’ quantity of media and the fact that social network users continuously add new images and create new terms. We will review the state of the art approaches to automatic annotation and tag refinement for social images, considering also the temporal patterns of their usage, and discuss extensions to tag suggestion and localization in web video sequences.
2015
74
1443
1468
Lamberto Ballan; Marco Bertini; Tiberio Uricchio; Alberto Del Bimbo
File in questo prodotto:
File Dimensione Formato  
Ballan2015_Article_Data-drivenApproachesForSocial.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 3.46 MB
Formato Adobe PDF
3.46 MB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/917330
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 18
social impact