Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality

Area of Science:

• Computer Science
• Human-Computer Interaction
• Artificial Intelligence

Background:

• Emotion recognition is crucial for human-computer interaction, relying on non-verbal cues like facial expressions.
• Accurate emotion detection requires robust algorithms and sensitive sensors for high-quality input.
• Automating human emotion recognition can enhance social intelligence in machines.

Purpose of the Study:

• To survey various approaches and techniques for emotion recognition.
• To introduce the Microsoft HoloLens (MHL) for emotion recognition in Augmented Reality (AR).
• To compare the performance of the MHL with a standard webcam for emotion detection.

Main Methods:

• Review of existing emotion recognition databases and algorithms for facial expression analysis.
• Introduction and sensor analysis of the Microsoft HoloLens (MHL) for AR applications.
• Preliminary emotion recognition experiments using the MHL and a conventional webcam.

Main Results:

• The Microsoft HoloLens (MHL) demonstrates potential for emotion recognition in Augmented Reality (AR).
• Preliminary findings indicate the MHL's emotion recognition capabilities are comparable to a regular webcam.
• Sensor data from the MHL provides valuable input for affective computing.

Conclusions:

• The Microsoft HoloLens (MHL) is a viable tool for emotion recognition research in AR.
• Further research is needed to fully leverage MHL's sensor capabilities for enhanced emotion detection.
• Comparing MHL with traditional methods like webcams provides insights into sensor-based emotion recognition advancements.