董莹莹, 赵 星, 王纪华. 基于GPU的虚拟植物生长的双尺度自动机模型实现方法[J]. 农业工程学报, 2011, 27(5): 207-212.
    引用本文: 董莹莹, 赵 星, 王纪华. 基于GPU的虚拟植物生长的双尺度自动机模型实现方法[J]. 农业工程学报, 2011, 27(5): 207-212.
    Dong Yingying, Zhao Xing, Wang Jihua. Rendering plants with dual-scale automaton model based on GPU[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(5): 207-212.
    Citation: Dong Yingying, Zhao Xing, Wang Jihua. Rendering plants with dual-scale automaton model based on GPU[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(5): 207-212.

    基于GPU的虚拟植物生长的双尺度自动机模型实现方法

    Rendering plants with dual-scale automaton model based on GPU

    • 摘要: 为提高双尺度自动机模型绘制植物图形的速度,给出其基于图形处理器(GPU)的并行实现方法。该方法将拓扑结构与归一化植物器官相结合构造三维植物图形:首先在GPU顶点着色器(vertex shader)中构造拓扑结构,然后在GPU几何着色器(geometry shader)中实现几何造型,最后将几何结构数据渲染到帧缓存中显示。选取植物学家给出的一株白杨进行基于GPU的生长模拟试验。结果显示,随绘制顶点数的增加,采用GPU进行绘制,相对CPU而言,其加速比可以从几倍扩大到十几倍以上。该方法可进一步应用于大规模自然场景绘制、虚拟农业等领域。

       

      Abstract: In order to accelerate plants rendering of dual-scale automaton model, a method based on GPU was proposed for model realization. In this method, the 3D structure of plant was constructed by combining with topological structure and normalized plant organs. Firstly, topological structure was constructed in vertex shader, then geometrical structure was built in geometry shader, and finally geometrical structure was transfered to frame buffer for displaying. The GPU-based method was tested by rendering a poplar tree. In the experiment, as the point number multiplied, the speed-up ratio of GPU rendering relative to CPU rendering could increase several-fold and even ten times. The results not only adequately showed the effectiveness of this GPU-based rendering method, but also fully represented its remarkable improvement in computation. Moreover, rendering plants with dual-scale automaton model based on GPU can be applied to natural scenery rendering, virtual agriculture, computer-aided design etc, which involves enormous data.

       

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