Learning to Control an Android Robot Head for Facial Animation
This work addresses the challenge of creating realistic facial animations for human-like robotic heads, though it is incremental as it applies and modifies an existing method to a different robot.
The authors tackled the problem of mapping facial expressions from human actors onto an android robot head by using 3D landmarks and pairwise distances as input instead of facial action units, resulting in participants preferring their approach in most cases in an online survey.
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.