用函数组合生成可表达情感的动画，让代码创作更直观。
fog: Expressing Motion and Emotion through Function Composition of AI-Generated Code
- 通过函数组合构建动作与情绪表达的代码框架
- 用户识别动作语义准确率达68%，是随机水平的2.68倍
- 支持新手与专家快速迭代，提升创作控制力
动作与情感是智能表达行为的核心。本文提出 fog，一个用于实现和组合动作函数的函数式框架。我们展示了如何利用 fog 在海德-西梅尔风格动画中表达动作与情感。该代码生成框架可帮助用户生成动词、副词、手势和情绪相关的函数，构建开放的动作词汇库。配套的动画编辑器支持直接操作与动态生成的用户界面，便于精细调整。通过感知评估，我们测试了452个 fog 生成的动画，发现人类对动作语义的识别准确率为68%，相比随机基线提升了2.68倍。在包含专业人士与新手的混合方法用户研究中，我们验证了 fog 界面能有效支持更快的迭代、探索与控制。
原文摘要 · Abstract (English)
Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implementing and compose motion functions. We demonstrate how fog can be used to express motion and emotion in Heider-Simmel style animations. This code generation framework can help users generate functions for verbs, adverbs, gestures, and emotions to create an open-ended motion vocabulary. It is complemented by an animation editor that helps users refine motion through direct manipulation and dynamically generated UI. We evaluate our approach with a perceptual evaluation, where we test 452 fog-generated animations to see if people can recognize the semantic meaning of the motion. We find that fog's motion functions can be recognized at 68% accuracy, a 2.68x improvement over a chance baseline. In a mixed-methods user study with professionals and novices, we show that fog in interface form can support users with more rapid iteration, exploration, and control.
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