NPAR16

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https://diglib.eg.org/handle/10.2312/15069

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Browsing NPAR16 by Subject "Enhancement"

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    Art-directed Watercolor Rendered Animation
    (The Eurographics Association, 2016) Montesdeoca, Santiago E.; Seah, Hock-Soon; Rall, Hans-Martin; Pierre Bénard and Holger Winnemöller
    This paper presents a system to render 3D animated geometry as watercolor painted animation with art-directed control. Our approach focuses on letting the end user paint the influence of the modeled watercolor effects in the 3D scene to simulate the characteristic appearance of traditional watercolor. For this purpose, it performs an object-space simulation and makes use of the user-painted influences to control and enhance image-space watercolor effects. In contrast to previous approaches, we introduce specialized watercolor shaders that are adjusted and deformed according to the desired painted effects. We further present novel algorithms that simulate hand tremors, pigment turbulence, color bleeding, edge darkening, paper distortion and granulation. All of these represent essential characteristic effects of traditional watercolor. The system performs in real-time, scales well with scene complexity and is fully implemented in Autodesk Maya.
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    Automatic Texture Guided Color Transfer and Colorization
    (The Eurographics Association, 2016) Arbelot, Benoit; Vergne, Romain; Hurtut, Thomas; Thollot, Joëlle; Pierre Bénard and Holger Winnemöller
    This paper targets two related color manipulation problems: Color transfer for modifying an image's colors and colorization for adding colors to a grayscale image. Automatic methods for these two applications propose to modify the input image using a reference that contains the desired colors. Previous approaches usually do not target both applications and suffer from two main limitations: possible misleading associations between input and reference regions and poor spatial coherence around image structures. In this paper, we propose a unified framework that uses the textural content of the images to guide the color transfer and colorization. Our method introduces an edge-aware texture descriptor based on region covariance, allowing for local color transformations. We show that our approach is able to produce results comparable or better than state-of-the-art methods in both applications.