Human Emotion Estimation Using Multi-Modal Variational AutoEncoder with Time Changes - Moroto, Yuya; Maeda, Keisuke; Ogawa, Takahiro; Haseyama, Miki (2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech), 2021)
A human emotion estimation method via feature integration using multi-modal variational autoencoder (MVAE) with time changes is presented in this paper. To utilize multimodal information such as gaze and brain activity data including some noises, the proposed method newly introduces MVAE into the human emotion estimation. Furthermore, the proposed MVAE can consider the changes in bio-signals with time and reduce the effect of noises caused in bio-signals by using the probabilistic variation. Experimental results with that of some state-of-the-art methods indicate that the proposed method is effective.