Action-Affect-Gender Classification Using Multi-task Representation Learning

@article{Shields2017ActionAffectGenderCU,
  title={Action-Affect-Gender Classification Using Multi-task Representation Learning},
  author={Timothy J. Shields and Mohamed R. Amer and Max Ehrlich and Amir Tamrakar},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2017},
  pages={2249-2258}
}
Recent work in affective computing focused on affect from facial expressions, and not as much on body. This work focuses on body affect. Affect does not occur in isolation. Humans usually couple affect with an action; for example, a person could be running and happy. Recognizing body affect in sequences requires efficient algorithms to capture both the… CONTINUE READING