A Mixture of Personalized Experts for Human Affect Estimation
Published in MLDM, 2018
Recommended citation: Feffer M., Rudovic O., Picard R.W. (2018) A Mixture of Personalized Experts for Human Affect Estimation. In: Perner P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2018. Lecture Notes in Computer Science, vol 10935. Springer, Cham. https://dspace.mit.edu/bitstream/handle/1721.1/129494/personalized-mixture-supervised_final_tYWcW0Y.pdf?sequence=2&isAllowed=y
We investigate the personalization of deep convolutional neural networks for facial expression analysis from still images. While prior work has focused on population-based (“one-size-fits-all”) approaches, we formulate and construct personalized models via a mixture of experts and supervised domain adaptation approach, showing that it improves greatly upon non-personalized models.
Recommended citation: Feffer M., Rudovic O., Picard R.W. (2018) A Mixture of Personalized Experts for Human Affect Estimation. In: Perner P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2018. Lecture Notes in Computer Science, vol 10935. Springer, Cham.