By chance is not enough: Preserving relative density through non uniform sampling

Enrico Bertini, Giuseppe Santucci

    Research output: Contribution to journalConference articlepeer-review

    Abstract

    Dealing with visualizations containing large data set is a challenging issue and, in the field of Information Visualization, almost every visual technique reveals its drawback when visualizing large number of items. To deal with this problem we introduce a formal environment, modeling in a virtual space the image features we are interested in (e.g, absolute and relative density, clusters, etc.) and we define some metrics able to characterize the image decay. Such metrics drive our automatic techniques (i.e., not uniform sampling) rescuing the image features and making them visible to the user. In this paper we focus on 2D scatter-plots, devising a novel non uniform data sampling strategy able to preserve in an effective way relative densities.

    Original languageEnglish (US)
    Pages (from-to)622-629
    Number of pages8
    JournalProceedings of the International Conference on Information Visualization
    Volume8
    StatePublished - 2004
    EventProceedings - Eighth International Conference on Information Visualisation, IV 2004 - London, United Kingdom
    Duration: Jul 14 2004Jul 16 2004

    Keywords

    • Metrics
    • Non-uniform sampling
    • Visual clutter

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Computer Vision and Pattern Recognition

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