基于神经网络的小提琴手手部动画

Junh-Nam Kim, Frédéric Cordier, N. Magnenat-Thalmann
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引用次数: 30

摘要

我们提出了一个系统的动画人手拉小提琴。一个神经网络控制手的运动。我们利用一种优化方法来生成用于神经网络训练的样例。使用哪个手指的音乐决定是通过最佳第一搜索自动做出的。我们展示了小提琴手的动作在物理上和音乐上是可行的,并且音乐上的决定与小提琴教育学中推荐的一致。给出了系统的描述、决策结果和动画。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network-based violinist's hand animation
We present a system for the animation of a human hand that plays violin. A neural network controls the hand movement. We make use of an optimization method to generate examples for the neural network training. The musical decision of which finger to use is automatically made by best first search. We show that the movements of the violinist's hands are physically and musically feasible, and that the musical decisions are consistent with those recommended in the violin pedagogy. A description of the system, the results of the decisions, and the animations are presented.
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