Transfer learning to account for idiosyncrasy in face and body expressions

  title={Transfer learning to account for idiosyncrasy in face and body expressions},
  author={Bernardino Romera-Paredes and M. S. Hane Aung and Massimiliano Pontil and Nadia Bianchi-Berthouze and Amanda C. de C. Williams and Paul J. Watson},
  journal={2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)},
In this paper we investigate the use of the Transfer Learning (TL) framework to extract the commonalities across a set of subjects and also to learn the way each individual instantiates these commonalities to model idiosyncrasy. To implement this we apply three variants of Multi Task Learning, namely: Regularized Multi Task Learning (RMTL), Multi Task Feature Learning (MTFL) and Composite Multi Task Feature Learning (CMTFL). Two datasets are used; the first is a set of point based facial… CONTINUE READING
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