让机器人实时识别人群情绪，提升交互自然度。
Multi-face emotion detection for effective Human-Robot Interaction
- 在移动端部署多人脸情绪识别模型，支持实时检测
- 对比多种深度模型，平衡准确率与内存占用
- 适合人机交互、服务机器人研发人员参考
移动设备中的对话接口已广泛应用，提供多样服务。随着技术进步，具备类人特征的拟人机器人日益受到重视，先进人机对话接口的应用持续扩展。在此背景下，情绪识别对提升人机交互至关重要，使机器人能够理解人类意图。本研究提出一种集成于移动拟人机器人的面部情绪检测界面，可在用户界面上实时显示多人的情绪状态。为此，开发并评估了多种用于面部表情识别的深度神经网络模型，在一致的计算机条件下获得良好效果。随后，仔细权衡了准确率与内存占用之间的平衡，以实现该应用在移动拟人机器人上的有效部署。
原文摘要 · Abstract (English)
The integration of dialogue interfaces in mobile devices has become ubiquitous, providing a wide array of services. As technology progresses, humanoid robots designed with human-like features to interact effectively with people are gaining prominence, and the use of advanced human-robot dialogue interfaces is continually expanding. In this context, emotion recognition plays a crucial role in enhancing human-robot interaction by enabling robots to understand human intentions. This research proposes a facial emotion detection interface integrated into a mobile humanoid robot, capable of displaying real-time emotions from multiple individuals on a user interface. To this end, various deep neural network models for facial expression recognition were developed and evaluated under consistent computer-based conditions, yielding promising results. Afterwards, a trade-off between accuracy and memory footprint was carefully considered to effectively implement this application on a mobile humanoid robot.
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