Emotional expression perception and categorization are extremely popular in the affective computing community. However, the inclusion of emotions in the decision-making process of an agent is not considered in most of the research in this field. To treat emotion expressions as the final goal, although necessary, reduces the usability of such solutions in more complex scenarios. To create a general affective model to be used as a modulator for learning different cognitive tasks, such as modeling intrinsic motivation, creativity, dialog processing, grounded learning, and human-level communication, instantaneous emotion perception cannot be the pivotal focus.

This book aims to present recent contributions for multimodal emotion recognition and empathy prediction which take into consideration the long-term development of affective concepts. On this regard, we provide access to two datasets: the OMG-Emotion Behavior Recognition and OMG-Empathy Prediction datasets. These datasets were designed, collected and formalized to be used on the OMG-Emotion Recognition Challenge and the OMG-Empathy Prediction challenge, respectively. All the participants of our challenges are invited to submit their contribution to our book. We also invite interested authors to use our datasets on the development of inspiring and innovative research on affective computing. By formatting these solutions and editing this book, we hope to inspire further research in affective and cognitive computing over longer timescales.

Website: https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/OMGBook2018.html

Submission Guidelines 

All submissions should be done via EasyChair: https://easychair.org/conferences/?conf=omgbook2018

Original artwork and a signed copyright release form will be required for all accepted chapters. For author instructions, please visit: https://www.springer.com/us/authors-editors/book-authors-editors/resources-guidelines/book-manuscript-guidelines

List of Topics

• New theories and findings on continuous emotion recognition
• Multi- and cross-modal emotion perception and interpretation
• Novel neural network models for affective processing
• Lifelong affect analysis, perception, and interpretation
• New neuroscientific and psychological findings on continuous emotion representation
• Embodied artificial agents for empathy and emotion appraisal
• Machine learning for affect-driven interventions
• Socially intelligent human-robot interaction
• Personalized systems for human affect recognition
• New theories and findings on empathy modelling
• Multimodal processing of empathetic and social signals
• Novel neural network models for empathy understanding
• Lifelong models for empathetic interactions
• Empathetic Human-Robot-Interaction (HRI) scenarios
• New neuroscientific and psychological findings on empathy representation
• Multi-agent communication for empathetic interactions
• Empathy as a decision-making modulator
• Personalized systems for empathy prediction

Editors

Organizing committee

• Dr. Pablo Barros, University of Hamburg, Germany
• Prof. Stefan Wermter, University of Hamburg, Germany

Publication

The volume will be published by Springer Series on Competitions in Machine Learning

Contact

All questions about submissions should be emailed to barros@informatik.uni-hamburg.de