In Face-to-Face communication, his or her face is an important part that decides the impression of a person because a person estimates the personality of the interlocutor from the features of the face of the interlocutor. Therefore, we made a hypothesis own impression and personality of giving to others by changing the own face freely. Then we proposed the e2-Mask that a mask-type display that synchronizes with facial expressions and substitutes an avatar for a human face.

This paper presents a thin digital full-face mask display that can reflect an entire facial expression of a user onto an avatar to support augmented face-to-face communication in real environments. Although camera-based facial expression recognition technology has enabled people to augment their faces with avatars, application was limited to face-to-face communication in virtual environments. To enable digital facial augmentation with an avatar in a real space, we propose a digital face mask display system that integrates a lightweight flexible display with a thin facial expression recognition system. The thin wearable facial expression recognition system was implemented with photo reflective sensor arrays which can measure facial expressions at 40 feature points distributed across an entire face. We investigated a ten-class facial expression identification model based on an SVM training algorithm. The trained model achieved an average accuracy of 79% when identifying the facial expressions of multiple users. User experiments indicated that the proposed thin digital full-face mask display allows the wearer to control the facial expression of the avatar with a fast response rate and create a positive sense of self-agency and self-ownership toward the augmented avatar face.

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