用实时表情与头部动作模仿，让机器人更自然地互动。
Real-Time Imitation of Human Head Motions, Blinks and Emotions by Nao Robot: A Closed-Loop Approach
- 结合MediaPipe与DeepFace，实时捕捉人类头部动作与表情
- 闭合回路反馈使姿态模仿的R2得分达96.3（俯仰）和98.9（偏航）
- 适合自闭症儿童沟通训练，提升人机交互体验
本文提出一种新方法，使Nao机器人能够实时模仿人类头部运动，重点提升人机交互质量。通过使用MediaPipe计算机视觉库和DeepFace情绪识别库，系统可精准捕捉人类头部动作、眨眼及情感表达，并将这些特征无缝融入机器人响应中。该框架采用闭环机制，实时获取机器人模仿效果反馈，显著提升建模精度：俯仰角（pitch）R2得分为96.3，偏航角（yaw）达98.9。该方法在改善自闭症儿童沟通能力方面具有潜力，为有特殊交流需求者提供有效互动工具。研究整合了实时头部动作模仿与情绪识别，推动人机交互向更自然、更智能方向发展。
原文摘要 · Abstract (English)
This paper introduces a novel approach for enabling real-time imitation of human head motion by a Nao robot, with a primary focus on elevating human-robot interactions. By using the robust capabilities of the MediaPipe as a computer vision library and the DeepFace as an emotion recognition library, this research endeavors to capture the subtleties of human head motion, including blink actions and emotional expressions, and seamlessly incorporate these indicators into the robot's responses. The result is a comprehensive framework which facilitates precise head imitation within human-robot interactions, utilizing a closed-loop approach that involves gathering real-time feedback from the robot's imitation performance. This feedback loop ensures a high degree of accuracy in modeling head motion, as evidenced by an impressive R2 score of 96.3 for pitch and 98.9 for yaw. Notably, the proposed approach holds promise in improving communication for children with autism, offering them a valuable tool for more effective interaction. In essence, proposed work explores the integration of real-time head imitation and real-time emotion recognition to enhance human-robot interactions, with potential benefits for individuals with unique communication needs.
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