Qizhi Yu

National Institute for Research in Computer Science and Control, Le Chesney, Île-de-France, France

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Publications (5)2.07 Total impact

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    ABSTRACT: We present a feature-based vector simulation approach for simulating local wave phenomena which often appear in running streams. By using this approach, we simulate the quasi-stationary waves caused by obstacles in shallow water. The geomet- ric features of the waves are constructed and animated using vector representation. The vector data is then converted to feature aligned meshes for capturing the shape of the waves. Our approach provides high-resolution details with real-time performance, and allows users to intuitively control the simulation behavior. Key-words: Rivers, wave simulation, animation, phenomenological simulation, vec-
    Computer Animation and Virtual Worlds 01/2011; 22:91-98. · 0.44 Impact Factor
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    ABSTRACT: Texturing an animated fluid is a useful way to augment the visual complexity of pictures without increasing the simulation time. But texturing flowing fluids is a complex issue, as it creates conflicting requirements: we want to keep the key texture properties (features, spectrum) while advecting the texture with the underlying flow — which distorts it. In this paper, we present a new, Lagrangian, method for advecting textures: the advected texture is computed only locally and follows the velocity field at each pixel. The texture retains its local properties, including its Fourier spectrum, even though it is accurately advected. Due to its Lagrangian nature, our algorithm can perform on very large, potentially infinite scenes, with less than 10 ms per frame. Our experiments show that it is well suited for a wide range of input textures, including, but not limited to, noise textures.
    IEEE transactions on visualization and computer graphics. 12/2010;
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    ABSTRACT: Many recent games and applications target the interactive exploration of realistic large scale worlds. These worlds consist mostly of static terrain models, as the simulation of animated fluids in these virtual worlds is computation- ally expensive. Adding flowing fluids, such as rivers, to these virtual worlds would greatly enhance their realism, but causes specific issues: as the user is usually observing the world at close range, small scale details such as waves and ripples are important. However, the large scale of the world makes classical methods impractical for simulating these effects. In this paper, we present an algorithm for the interactive simulation of realistic flowing fluids in large virtual worlds. Our method relies on two key contributions: the local computation of the velocity field of a steady flow given boundary conditions, and the advection of small scale details on a fluid, following the velocity field, and uniformly sampled in screen space.
    Computer Graphics Forum 01/2009; · 1.64 Impact Factor
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    ABSTRACT: We present a feature-based vector simulation approach for simulating local wave phenomena which often appear in streams. By using this approach, we simulate the wave pattern in front of an obstacle in a flow. Based on laws in hydrodynamics, we present an efficient geometric construction method which can generate and animate the vector features of the target wave phenomenon. From the vector information, we are able to build feature aligned mesh for capturing the high-resolution details of the local waves. The results show that our approach is suitable for real-time applications. The approach also allows users to intuitively control the animation.
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    ABSTRACT: Texturing an animated fluid is a useful way to augment the visual complexity of pictures without increasing the simulation time. But texturing flowing fluids is a complex issue, as it creates conflicting requirements: we want to keep the texture properties (features, spectrum) while conforming to the underlying flow --- which distorts the attached texture. In this paper, we present a new method for texturing animated fluids. Our method ensures that the moving texture always follows the velocity field of the fluid, while maintaining key properties of the original texture. Our algorithm runs in real-time; our experiments show that it is well suited for a wide range of input texture, including, but not limited to, noise textures.