3 research outputs found

    Toward a Perceptually-relevant Theory of Appearance

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    Two approaches are commonly employed in Computer Graphics to design and adjust the appearance of objects in a scene. A full 3D environment may be created, through geometrical, material and lighting modeling, then rendered using a simulation of light transport; appearance is then controlled in ways similar to photography. A radically different approach consists in providing 2D digital drawing tools to an artist, whom with enough talent and time will be able to create images of objects having the desired appearance; this is obviously strongly similar to what traditional artists do, with the computer being a mere modern drawing tool.In this document, I present research projects that have investigated a third approach, whereby pictorial elements of appearance are explicitly manipulated by an artist. On the one side, such an alternative approach offers a direct control over appearance, with novel applications in vector drawing, scientific illustration, special effects and video games. On the other side, it provides an modern method for putting our current knowledge of the perception of appearance to the test, as well as to suggest new models for human vision along the way

    Inverse Diffusion Curves using Shape Optimization

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    © 1995-2012 IEEE. The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats

    Inverse Diffusion Curves Using Shape Optimization

    No full text
    © 1995-2012 IEEE. The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats
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