The Markov pen: online synthesis of free-hand drawing styles

Katrin Lang, M. Alexa
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引用次数: 16

Abstract

Learning expressive curve styles from example is crucial for interactive or computer-based narrative illustrations. We propose a method for online synthesis of free-hand drawing styles along arbitrary base paths by means of an autoregressive Markov Model. Choice on further curve progression is made while drawing, by sampling from a series of previously learned feature distributions subject to local curvature. The algorithm requires no user-adjustable parameters other than one short example style. It may be used as a custom "random brush" designer in any task that requires rapid placement of a large number of detail-rich shapes that are tedious to create manually.
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马尔科夫笔:在线合成的手绘风格
从例子中学习表达曲线风格对于交互式或基于计算机的叙事插图至关重要。我们提出了一种利用自回归马尔可夫模型沿任意基准路径在线合成手绘样式的方法。在绘制时,通过从一系列先前学习到的受局部曲率约束的特征分布中采样,来选择进一步的曲线级数。除了一个简短的示例样式外,该算法不需要用户可调整的参数。它可以用作自定义“随机刷”设计器,用于任何需要快速放置大量细节丰富的形状的任务,这些形状手动创建非常繁琐。
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