用3D关键点距离提升机器人面部表情的自然度
Learning to Control an Android Robot Head for Facial Animation
- 用3D关键点间距替代表情动作单元作为输入
- 在线调查中多数人更偏好新方法生成的表情
- 适合需要自然面部交互的仿人机器人研究者
展现丰富面部表情对类人机器人头部至关重要。尽管手动定义表情复杂，已有自动学习方法可实现。本文将一种已有方法应用于不同于原研究的机器人头部，为改善人类演员表情向机器人头部的映射，提出使用3D关键点及其成对距离作为学习算法输入，取代先前使用的面部动作单元。在线问卷调查结果显示，参与者在多数情况下更偏好新方法生成的表情，但仍有改进空间。
原文摘要 · Abstract (English)
The ability to display rich facial expressions is crucial for human-like robotic heads. While manually defining such expressions is intricate, there already exist approaches to automatically learn them. In this work one such approach is applied to evaluate and control a robot head different from the one in the original study. To improve the mapping of facial expressions from human actors onto a robot head, it is proposed to use 3D landmarks and their pairwise distances as input to the learning algorithm instead of the previously used facial action units. Participants of an online survey preferred mappings from our proposed approach in most cases, though there are still further improvements required.
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