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New Controls for Combining Images in Correspondence.

Jing Liao, Diego Nehab, Hugues Hoppe

    IEEE Transactions on Visualization and Computer Graphics
    |September 10, 2015
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    Summary
    This summary is machine-generated.

    This study introduces novel controls for image interpolation and morphing by applying edge-aware decomposition to correspondence maps. This creates intuitive parameter spaces for merging shape and color, enabling new hybrid image and video synthesis.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Computer Graphics

    Background:

    • Existing image interpolation methods often use simple geometric and color blending functions.
    • Defining correspondence maps for structurally similar elements is a key challenge in morphing.

    Purpose of the Study:

    • To explore new controls for combining images using correspondence maps.
    • To develop an intuitive framework for merging shape and color information from source images.
    • To enable interactive synthesis of hybrid images and video morphing.

    Main Methods:

    • Applied edge-aware decomposition techniques to correspondence maps, not just image content.
    • Developed a low-dimensional parameter space for merging shape and color at multiple frequencies.
    • Created a gallery-based user interface for interactive exploration and synthesis.

    Main Results:

    • Established an intuitive parameter space for merging image attributes.
    • Demonstrated compelling effects through extrapolation of shape parameters.
    • Extended the framework successfully to video interpolation.

    Conclusions:

    • The proposed framework offers enhanced control over image interpolation and morphing.
    • Edge-aware decomposition of correspondence maps is effective for richer image blending.
    • The method facilitates intuitive creation of hybrid imagery and video effects.