Innovation Owner
Mr. CHANNARONG SUWANNARAT
Student
Details
This study introduces an Ensemble Learning approach using Mixture of Experts (MoE) to improve Facial Expression Recognition (FER) robustness. The system effectively handles diverse environments and partial occlusions, outperforming traditional Averaging Ensemble methods.
Facial Expression Recognition (FER) has attracted considerable attention in fields such as healthcare, customer service, and behavior analysis. However, challenges remain in developing a robust system capable of adapting to various environments and dynamic situations.
In this study, the researchers introduced an Ensemble Learning approach to merge outputs from multiple models trained in specific conditions, allowing the system to retain old information while efficiently learning new data. This technique is advantageous in terms of training time and resource usage.
The study explores two main approaches to Ensemble Learning:
- Averaging Ensemble: Averaging outputs from dedicated models trained under specific scenarios.
- Mixture of Experts (MoE): A technique that combines multiple models each specialized in different situations.
Experimental results showed that Mixture of Experts (MoE) performs more effectively than the Averaging Ensemble method for emotion classification in all scenarios. The MoE system achieved an average accuracy of 84.41% on the CK+ dataset, 54.20% on Oulu-CASIA, and 61.66% on RAVDESS, significantly surpassing the performance of the Averaging Ensemble method.
Objective
The objectives are to develop a scalable emotion detection model capable of handling diverse data and to implement a system that selects specialized models to maintain accuracy during partial facial occlusions, such as glasses or mouth coverings.
- Develop a model for human emotion detection through facial expressions.
- Develop a system capable of efficient Scaling Up when incorporating data from various distinct scenarios.
- Develop a system capable of selecting models suitable for different types of partial facial occlusion, such as wearing glasses or mouth coverings.