Abstract

Human emotional and cognitive states evolve with variable intensity and clarity through the course of social interactions and experiences, and they are continuously influenced by a variety of input multimodal information from the environment and the interaction participants. This has motivated the development of a new area within affective computing that treats emotions as continuous variables and examines their representation, annotation and modeling. In this work, we use as a starting point the continuous emotional annotation that we performed on a large, multimodal database, and discuss annotation challenges, design decisions, annotation results and lessons learned from this effort, in the context of existing literature. Additionally, we discuss a variety of open questions for future research in terms of labeling, combining and processing continuous assessments of emotional and cognitive states.

Date

2013

Authors

Angeliki Metallinou, Shrikanth Narayanan

Source

2013 10th IEEE international conference and workshops on automatic face and gesture recognition (FG)

Pages

1-8

Publisher

IEEE