Springer Series on Competitions in Machine Learning

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.
TOPICS OF INTEREST
The topics of interest for this call for chapters include, but are not limited to:

- 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 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

Each contributed chapter is expected to present a novel research study, a comparative study, or a survey of the literature.
We also expect that each contributed chapter approach somehow at least one of our datasets: the OMG-Emotion and the OMG-Empathy.

SUBMISSIONS
All submissions should be done via EasyChair: https://easychair.org/conferences/?conf=deepbio2019 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

ACCESS TO THE DATASETS
- OMG-EMOTION - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_emotion.html
- OMG-EMPATHY - https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html


IMPORTANT DATES:
- Submission of abstracts: 18th of January 2019
- Notification of initial editorial decisions: 25th of January 2019
- Submissions of full-lenght chapters: 01st of March 2019
- Notification of final editorial decisions 03rd of May 2019
- Submission of revised chapters: 07th of June, 2019
EDITORIAL BOARD:
Dr. Pablo Barros, University of Hamburg, Germany Prof. Stefan Wermter, University of Hamburg, Germany