Summarised presentation of personal photo sets

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

2 Citations (Scopus)

Abstract

People produce an increasing amount of digital photos to document events. Searching for a specific event can result in more photos than people can handle, making difficult judging their relevance. This paper presents a new algorithm, that summarises a set of photos described by attributes at different concept levels. It addresses the well-known human weakness to deal with large collections of distinct items, by presenting a low cardinality partition set. Each group yields a compact, yet distinct, description. The evaluation, including user tests, shows the algorithm outperforms others in context separation and informative power about the set being summarised.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings
Pages195-206
Number of pages12
Volume8325 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2014
Event20th Anniversary International Conference on MultiMedia Modeling, MMM 2014 - Dublin, Ireland
Duration: 6 Jan 201410 Jan 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8325 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference20th Anniversary International Conference on MultiMedia Modeling, MMM 2014
Country/TerritoryIreland
CityDublin
Period6/01/1410/01/14

Keywords

  • Attribute induction
  • Clustering algorithm
  • Human factors
  • Multimedia summarisation

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