Automatic Privacy Classification of Personal Photos - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

Automatic Privacy Classification of Personal Photos

Résumé

Tagging photos with privacy-related labels, such as “myself”, “friends” or “public”, allows users to selectively display pictures appropriate in the current situation (e.g. on the bus) or for specific groups (e.g. in a social network). However, manual labelling is time-consuming or not feasible for large collections. Therefore, we present an approach to automatically assign photos to privacy classes. We further demonstrate a study method to gather relevant image data without violating participants’ privacy. In a field study with 16 participants, each user assigned 150 personal photos to self-defined privacy classes. Based on this data, we show that a machine learning approach extracting easily available metadata and visual features can assign photos to user-defined privacy classes with a mean accuracy of 79.38 %.
Fichier principal
Vignette du fichier
346942_1_En_33_Chapter.pdf (376.44 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01599867 , version 1 (02-10-2017)

Licence

Paternité

Identifiants

Citer

Daniel Buschek, Moritz Bader, Emanuel Von Zezschwitz, Alexander De Luca. Automatic Privacy Classification of Personal Photos. 15th Human-Computer Interaction (INTERACT), Sep 2015, Bamberg, Germany. pp.428-435, ⟨10.1007/978-3-319-22668-2_33⟩. ⟨hal-01599867⟩
106 Consultations
391 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More