• Login
    View Item 
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 38 (2019)
    • 38-Issue 3
    • View Item
    •   Eurographics DL Home
    • Computer Graphics Forum
    • Volume 38 (2019)
    • 38-Issue 3
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    ClustMe: A Visual Quality Measure for Ranking Monochrome Scatterplots based on Cluster Patterns

    Thumbnail
    View/Open
    v38i3pp225-236.pdf (2.143Mb)
    1290-file1.pdf (3.919Mb)
    Date
    2019
    Author
    Abbas, Mostafa M.
    Aupetit, Michaël ORCID
    Sedlmair, Michael
    Bensmail, Halima
    Pay-Per-View via TIB Hannover:

    Try if this item/paper is available.

    Metadata
    Show full item record
    Abstract
    We propose ClustMe, a new visual quality measure to rank monochrome scatterplots based on cluster patterns. ClustMe is based on data collected from a human-subjects study, in which 34 participants judged synthetically generated cluster patterns in 1000 scatterplots. We generated these patterns by carefully varying the free parameters of a simple Gaussian Mixture Model with two components. and asked the participants to count the number of clusters they could see (1 or more than 1). Based on the results, we form ClustMe by selecting the model that best predicts these human judgments among 7 different state-of-the-art merging techniques (DEMP). To quantitatively evaluate ClustMe, we conducted a second study, in which 31 human subjects ranked 435 pairs of scatterplots of real and synthetic data in terms of cluster patterns complexity. We use this data to compare ClustMe's performance to 4 other state-of-the-art clustering measures, including the well-known Clumpiness scagnostics. We found that of all measures, ClustMe is in strongest agreement with the human rankings.
    BibTeX
    @article {10.1111:cgf.13684,
    journal = {Computer Graphics Forum},
    title = {{ClustMe: A Visual Quality Measure for Ranking Monochrome Scatterplots based on Cluster Patterns}},
    author = {Abbas, Mostafa M. and Aupetit, Michaël and Sedlmair, Michael and Bensmail, Halima},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13684}
    }
    URI
    https://doi.org/10.1111/cgf.13684
    https://diglib.eg.org:443/handle/10.1111/cgf13684
    Collections
    • 38-Issue 3

    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA
     

     

    Browse

    All of Eurographics DLCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    BibTeX | TOC

    Create BibTeX Create Table of Contents

    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA