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Does organisation by similarity assist image browsing?

Published: 01 March 2001 Publication History

Abstract

In current systems for browsing image collections, users are presented with sets of thumbnail images arranged in some default order on the screen. We are investigating whether it benefits users to have sets of thumbnails arranged according to their mutual similarity, so images that are alike are placed together. There are, of course, many possible definitions of “similarity”: so far we have explored measurements based on low-level visual features, and on the textual captions assigned to the images. Here we describe two experiments, both involving designers as the participants, examining whether similarity-based arrangements of the candidate images are helpful for a picture selection task. Firstly, the two types of similarity-based arrangement were informally compared. Then, an arrangement based on visual similarity was more formally compared with a control of a random arrangement. We believe this work should be of interest to anyone designing a system that involves presenting sets of images to users.

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cover image ACM Conferences
CHI '01: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
March 2001
559 pages
ISBN:1581133278
DOI:10.1145/365024
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 March 2001

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Author Tags

  1. evaluation
  2. image retrieval
  3. information visualisation

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CHI '01 Paper Acceptance Rate 69 of 352 submissions, 20%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

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  • (2022)Fusion of Multi-Modal Underwater Ship Inspection Data with Knowledge GraphsOCEANS 2022, Hampton Roads10.1109/OCEANS47191.2022.9977371(1-9)Online publication date: 17-Oct-2022
  • (2022)An overview of cluster-based image search result organization: background, techniques, and ongoing challengesKnowledge and Information Systems10.1007/s10115-021-01650-9Online publication date: 11-Feb-2022
  • (2021)Photo Sequences of Varying Emotion: Optimization with a Valence-Arousal Annotated DatasetACM Transactions on Interactive Intelligent Systems10.1145/345884411:2(1-19)Online publication date: 21-Jul-2021
  • (2021)The MovieWall: A New Interface for Browsing Large Video CollectionsMultiMedia Modeling10.1007/978-3-030-67835-7_15(170-182)Online publication date: 21-Jan-2021
  • (2020)Assigning Rated Items to Locations in Non-List Display LayoutsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.287016426:2(1278-1291)Online publication date: 1-Feb-2020
  • (2020)DualSDF: Semantic Shape Manipulation Using a Two-Level Representation2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR42600.2020.00765(7628-7638)Online publication date: Jun-2020
  • (2019)A Semantic-Based Method for Visualizing Large Image CollectionsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.283548525:7(2362-2377)Online publication date: 1-Jul-2019
  • (2018)A Viewable Indexing Structure for the Interactive Exploration of Dynamic and Large Image CollectionsACM Transactions on Knowledge Discovery from Data10.1145/304701112:1(1-26)Online publication date: 31-Jan-2018
  • (2017)Presenting and visualizing image results for professional image searchersProceedings of the 31st British Computer Society Human Computer Interaction Conference10.14236/ewic/HCI2017.6(1-5)Online publication date: 3-Jul-2017
  • (2017)Improving Exploratory Search Experience through Hierarchical Knowledge GraphsProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080829(145-154)Online publication date: 7-Aug-2017
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