论文标题
DualSmoke：基于草图的烟雾插图设计，具有两阶段生成模型
DualSmoke: Sketch-Based Smoke Illustration Design with Two-Stage Generative Model
论文作者
论文摘要
烟雾的动态影响在插图设计中令人印象深刻，但对于普通用户来说，在没有流体模拟的领域知识的情况下设计烟雾效应是一个麻烦且具有挑战性的问题。在这项工作中，我们提出了DualSmoke，这是互动烟雾插图设计的两阶段全球到本地生成框架。对于全球阶段，提出的方法利用流体模式从用户的手绘草图中生成拉格朗日连贯的结构。对于本地阶段，详细的流动模式是从生成的相干结构中获得的。最后，我们将引导力场应用于烟雾模拟器，以设计所需的烟雾插图。为了构建训练数据集，DualSmoke使用速度字段的有限时间Lyapunov指数生成流程模式。合成草图数据是通过骨架提取从流量模式生成的。从我们的用户研究中，可以验证拟议的设计界面可以提供各种烟雾插图设计，并具有良好的用户可用性。我们的代码可在以下网址找到：https：//github.com/shasph/dualsmoke
The dynamic effects of smoke are impressive in illustration design, but it is a troublesome and challenging issue for common users to design the smoke effect without domain knowledge of fluid simulations. In this work, we propose DualSmoke, two stage global-to-local generation framework for the interactive smoke illustration design. For the global stage, the proposed approach utilizes fluid patterns to generate Lagrangian coherent structure from the user's hand-drawn sketches. For the local stage, the detailed flow patterns are obtained from the generated coherent structure. Finally, we apply the guiding force field to the smoke simulator to design the desired smoke illustration. To construct the training dataset, DualSmoke generates flow patterns using the finite-time Lyapunov exponents of the velocity fields. The synthetic sketch data is generated from the flow patterns by skeleton extraction. From our user study, it is verified that the proposed design interface can provide various smoke illustration designs with good user usability. Our code is available at: https://github.com/shasph/DualSmoke
