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Image clustering based on a shared nearest neighbors approach for tagged collections

Published: 07 July 2008 Publication History

Abstract

Browsing and finding pictures in large-scale and heterogeneous collections is an important issue, most particularly for online photo sharing applications. Since such services are experiencing rapid growth of their databases, the tag-based indexing strategy and the results displayed in a traditional matrix representation may not be optimal for browsing and querying image collections. Naturally, unsupervised data clustering appeared as a good solution by presenting a summarized view of an image set instead of an exhaustive but useless list of its element. We present a new method for extracting meaningful and representative clusters based on a shared nearest neighbors (SNN) approach that treats both content-based features and textual descriptions (tags). We describe, discuss and evaluate the SNN method for image clustering and present some experimental results using the Flickr collections showing that our approach extracts representative information of an image set.

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cover image ACM Conferences
CIVR '08: Proceedings of the 2008 international conference on Content-based image and video retrieval
July 2008
674 pages
ISBN:9781605580708
DOI:10.1145/1386352
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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Publication History

Published: 07 July 2008

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Author Tags

  1. information retrieval and browsing
  2. multimedia indexing
  3. unsupervised data categorization

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  • (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
  • (2019)A novel multimodal clustering framework for images with diverse associated textMultimedia Tools and Applications10.1007/s11042-018-7131-x78:13(17623-17652)Online publication date: 1-Jul-2019
  • (2018)Shared Nearest Neighbor Clustering in a Locality Sensitive Hashing FrameworkJournal of Computational Biology10.1089/cmb.2017.011325:2(236-250)Online publication date: Feb-2018
  • (2017)Spectral-Density-Based Graph Construction Techniques for Hyperspectral Image AnalysisIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2017.271854755:10(5966-5983)Online publication date: Oct-2017
  • (2016)Demo of the SICOS tool for Social Image Cluster-based Organization and Search2016 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET)10.1109/IMCET.2016.7777452(202-206)Online publication date: Nov-2016
  • (2016)Scalable Parallel Algorithms for Shared Nearest Neighbor Clustering2016 IEEE 23rd International Conference on High Performance Computing (HiPC)10.1109/HiPC.2016.018(72-81)Online publication date: Dec-2016
  • (2016)Personalized Social Image Organization, Visualization, and Querying Tool Using Low- and High-Level Features2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES)10.1109/CSE-EUC-DCABES.2016.199(287-294)Online publication date: Aug-2016
  • (2016)Analyzing Flickr metadata to extract location-based information and semantically organize its photo contentNeurocomputing10.1016/j.neucom.2014.12.104172(114-133)Online publication date: Jan-2016
  • (2016)A survey on Flickr multimedia research challengesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2016.01.00651:C(71-91)Online publication date: 1-May-2016
  • (2016)Outlier Robust Geodesic K-means Algorithm for High Dimensional DataStructural, Syntactic, and Statistical Pattern Recognition10.1007/978-3-319-49055-7_23(252-262)Online publication date: 5-Nov-2016
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