A new database and protocol for image reuse detection

Furkan Isikdogan, Ilhan Adıyaman, Alkım Almila Akdağ Salah, Albert Ali Salah*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The use of visual elements of an existing image while creating new ones is a commonly observed phenomenon in digital artworks. The practice, which is referred to as image reuse, is not an easy one to detect even with the human eye, less so using computational methods. In this paper, we study the automatic image reuse detection in digital artworks as an image retrieval problem. First, we introduce a new digital art database (BODAIR) that consists of a set of digital artworks that re-use stock images. Then, we evaluate a set of existing image descriptors for image reuse detection, providing a baseline for the detection of image reuse in digital artworks. Finally, we propose an image retrieval method tailored for reuse detection, by combining saliency maps with the image descriptors.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2016 Workshops, Proceedings
EditorsGang Hua, Hervé Jégou
PublisherSpringer
Pages903-916
Number of pages14
ISBN (Print)9783319466033
DOIs
Publication statusPublished - 1 Jan 2016
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: 8 Oct 201616 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9913 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th European Conference on Computer Vision, ECCV 2016
Country/TerritoryNetherlands
CityAmsterdam
Period8/10/1616/10/16

Keywords

  • BODAIR
  • DeviantArt
  • Digital art
  • Feature extraction
  • Image database
  • Image retrieval
  • Image reuse

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