Motivation and workshop topics
Building intelligent artificial companions capable to interact with humans in the same way humans interact with each other is a major challenge in affective computing. Such a type of interactive companion must be capable of perceiving and interpreting multimodal information about the user in order to be able to produce an appropriate response. The proposed workshop mainly focuses on pattern recognition and machine learning methods for the perception of the user’s affective states, activities and intentions.

Workshop topics include, but are not limited to:

A. Algorithms to recognize emotions, behaviors, activities and intentions

• Facial expression recognition
• Recognition of gestures, head/body poses
• Audiovisual emotion recognition
• Analysis of bio-physiological data for emotion recognition
• Multimodal information fusion architectures
• Multi classifier systems and multi view classifiers
• Gesture recognition, activity recognition, behavior recognition
• Temporal information fusion

B. Learning Algorithms for social signal processing

• Learning from unlabeled and partially labeled data
• Learning with noisy/uncertain labels
• Deep learning architectures
• Learning of time series

C. Applications relevant to the workshop

• Companion technologies
• Robotics
• Assistive systems

D. Benchmark data sets relevant to workshop topics

Submission

Authors can submit their papers via the EasyChair submission system:

https://easychair.org/account/signin?l=3999137930385846043.1776702077.3e86a10b

Submissions must be prepared according to the Springer LNCS/LNAI. The length of the final paper will be limited to 6-8 Pages. Each paper will be peer-reviewed by at least three experts in the field for originality, significance, clarity, impact, and soundness.

Important Dates

Paper submission: May 29, 2026

Paper notification: June 05, 2026

Camera ready deadline: June 18, 2026

Workshop program finalized: TBA

Workshop date: TBA