EG2018

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https://diglib.eg.org/handle/10.2312/2632158

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Browsing EG2018 by Subject "Applied computing"

Now showing 1 - 4 of 4
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    Growing Circles: A Region Growing Algorithm for Unstructured Grids and Non-aligned Boundaries
    (The Eurographics Association, 2018) Dabbaghchian, Saeed; Jain, Eakta and Kosinka, JirĂ­
    Detecting the boundaries of an enclosed region is a problem which arises in some applications such as the human upper airway modeling. Using of standard algorithms fails because of the inevitable errors, i.e. gaps and overlaps between the surrounding boundaries. Growing circles is an automatic approach to address this problem. A circle is centered inside the region and starts to grow by increasing its radius. Its growth is limited either by the surrounding boundaries or by reaching its maximum radius. To deal with complex shapes, many circles are used in which each circle partially reconstructs the region, and the whole region is determined by the union of these partial regions. The center of the circles and their maximum radius are calculated adaptively. It is similar to the region growing algorithm which is widely used in image processing applications. However, it works for unstructured grids as well as Cartesian ones. As an application of the method, it is applied to detect the boundaries of the upper airway cross-sections.
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    Iterative Carving for Self-supporting 3D Printed Cavities
    (The Eurographics Association, 2018) Hornus, Samuel; Lefebvre, Sylvain; Diamanti, Olga and Vaxman, Amir
    Additive manufacturing technologies fabricate objects layer by layer, adding material on top of already solidified layers. A key challenge is to ensure that there is always material below, for otherwise added material simply falls under the effect of gravity. This is a critical issue with most technologies, and with fused filament in particular. In this work we investigate how to compute as large as possible empty cavities which boundaries are self-supporting. Our technique is based on an iterated carving algorithm, that is fast to compute and produces nested sets of inner walls. The walls have exactly the minimal printable thickness of the manufacturing process everywhere. Remarkably, our technique is out-of-core, sweeping through the model from the top down. Using our approach, we can print large objects using as little as a single filament thickness for the boundary, providing one order of magnitude reduction in print time and material use while guaranteeing printability.
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    A Smart Palette for Helping Novice Painters to Mix Physical Watercolor Pigments
    (The Eurographics Association, 2018) Chen, Mei-Yun; Yang, Ci-Syuan; Ouhyoung, Ming; Jain, Eakta and Kosinka, JirĂ­
    For novice painters, color mixing is a necessary skill which takes many years to learn. To get the skill easily, we design a system, a smart palette, to help them learn quickly. Our system is based on physical watercolor pigments, and we use a spectrometer to measure the transmittance and reflectance of watercolor pigments and collect a color mixing dataset. Moreover, we use deep neural network (DNN) to train a color mixing model. After that, using the model to predict a large amount of color mixing data creates a lookup table for color matching. In the smart palette, users can select a target color from an input image; then, the smart palette will find the nearest color, which is a matched color, and show a recipe where two pigments and their respective quantities can be mixed to get that color.
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    Time-Reversed Art Directable Smoke Simulation
    (The Eurographics Association, 2018) Oborn, Jeremy; Flynn, Sean; Egbert, Parris; Holladay, Seth; Diamanti, Olga and Vaxman, Amir
    Physics-based fluid simulation often produces unpredictable behavior that is difficult for artists to control. We present a new method for art directing smoke animation using time-reversed simulation. Given a final fluid configuration, our method steps backward in time generating a sequence that, when played forward, is visually similar to traditional forward simulations. This allows artists to create simulations with fast turnaround times that match an exact art-directed shape at any timestep of the simulation. We address a number of challenges associated with time-reversal including the problem of decreasing entropy.