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    We introduce decal-lenses, an interaction technique for exploring multivariate data on surfaces. This method allows real-time attribute selection and viewpoint changes, enhancing data visualization on complex geometries.

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    Area of Science:

    • Computer Science
    • Data Visualization
    • Human-Computer Interaction

    Background:

    • Traditional magic lenses are limited to 2D planes.
    • Visualizing multivariate data on complex 3D surfaces presents significant challenges.
    • Existing methods lack dynamic attribute management and spatial referencing on arbitrary geometries.

    Purpose of the Study:

    • To introduce decal-lenses, a novel interaction technique for augmenting and managing multivariate visualizations on arbitrary surfaces.
    • To enable users to explore data on complex geometries while maintaining spatial context and dynamic attribute control.
    • To extend interaction capabilities to intricate surfaces like the human brain using support surfaces.

    Main Methods:

    • Developed object-space lenses that conform to surface geometry, maintaining spatial references.
    • Implemented real-time attribute selection and combination within delimited lens regions.
    • Introduced support surfaces to facilitate lens placement on intricate and occluded geometries.
    • Extended region selection using brushing and lassoing operations.

    Main Results:

    • Decal-lenses allow users to explore multivariate data on arbitrary surfaces with dynamic attribute management.
    • The technique supports viewpoint changes during exploration while preserving spatial references to lens locations.
    • Support surfaces enable effective interaction with lenses on complex geometries, overcoming occlusion and holes.
    • Brushing and lassoing extend decal-lenses to arbitrary regions for customized data exploration.

    Conclusions:

    • Decal-lenses offer a powerful and flexible approach for interactive exploration of multivariate data on complex surfaces.
    • The technique enhances data analysis by providing localized attribute control and spatial context preservation.
    • Decal-lenses are applicable to various fields requiring detailed surface data visualization and interaction.