Data-driven finger motion synthesis for gesturing characters
Data-driven finger motion synthesis for gesturing characters
复制标题
用于手势字符的数据驱动手指运动合成
DOI：
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发表时间：
2012
影响因子：
6.2
通讯作者：
A. Safonova
中科院分区：
文献类型：
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作者：
S. Jörg;J. Hodgins;A. Safonova
捕捉演员的身体动作来为电影、游戏和VR应用程序创建动画已经成为标准做法，但手指动作通常是手动添加的，作为繁琐的后处理步骤。在这篇文章中，我们提供了一种令人惊讶的简单方法来自动执行这一步骤，以进行字符的手势和对话。在受控的环境中，我们仔细地捕捉和后处理来自多个演员的手指和身体动作。为了用真实和详细的手指动作来增强虚拟角色的身体动作，我们的方法从生成的数据库中选择手指动作片段，考虑到手臂动作的相似性和连续手指动作的流畅性。我们使用留一交叉验证来研究手臂运动的哪些部分最好地区分手势，并将结果作为选择合适的手指运动的度量。我们的方法对一些不同手势类型的例子提供了良好的结果，并在感知实验中得到了验证。
Capturing the body movements of actors to create animations for movies, games, and VR applications has become standard practice, but finger motions are usually added manually as a tedious post-processing step. In this paper, we present a surprisingly simple method to automate this step for gesturing and conversing characters. In a controlled environment, we carefully captured and post-processed finger and body motions from multiple actors. To augment the body motions of virtual characters with plausible and detailed finger movements, our method selects finger motion segments from the resulting database taking into account the similarity of the arm motions and the smoothness of consecutive finger motions. We investigate which parts of the arm motion best discriminate gestures with leave-one-out cross-validation and use the result as a metric to select appropriate finger motions. Our approach provides good results for a number of examples with different gesture types and is validated in a perceptual experiment.