Intuitive large image database browsing using perceptual similarity enriched by crowds

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The main objective of image browsers is to empower users to find a desired image with ease, speed and accuracy from a large database. In this paper we present a novel approach at creating an image browsing environment based on human perception with the aim of providing intuitive image navigation. In our approach, similarity judgments form the basic structural organization for the images in our browser. To enrich this we have developed a scalable crowd sourced method of augmenting a database with a large number of additional samples by capturing human judgments from members of a crowd. Experiments were conducted involving two databases that demonstrate the effectiveness of our method as an intuitive, fast browsing environment for large image databases.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages169-176
Number of pages8
Volume8048 LNCS
EditionPART 2
DOIs
Publication statusPublished - 26 Sep 2013
Event15th International Conference on Computer Analysis of Images and Patterns - York, United Kingdom
Duration: 27 Aug 201329 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8048 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference15th International Conference on Computer Analysis of Images and Patterns
Abbreviated titleCAIP 2013
CountryUnited Kingdom
CityYork
Period27/08/1329/08/13

    Fingerprint

Keywords

  • Abstracts
  • Browsers
  • Clustering
  • Crowd Sourcing
  • Databases
  • Images
  • Indexing
  • Navigation
  • Perception
  • Retrieval
  • Similarity
  • Textures

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Padilla, S., Halley, F., Robb, D. A., & Chantler, M. J. (2013). Intuitive large image database browsing using perceptual similarity enriched by crowds. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 8048 LNCS, pp. 169-176). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8048 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-40246-3_21