Pattern Recognition in Human-Machine-Interaction of the International Association for Pattern Recognition (IAPR). TC09 aims at promoting the use of pattern recognition methods in Human-machine interaction (HMI), and intends to offer an opportunity for interested researchers to gain a better understanding of the many diverse research topics in
remote sensing that require contributions from the pattern recognition community.
HMI typically takes place on a rather crude explicit question-answer level, whereas human-human interaction is multifaceted, and is consisting of manifold interactive feedback loops between interlocutors, comprising social components (e.g. display rules, social state), moods, feelings, personal goals, nonverbal and paralinguistic conversation channels and even more. In order to close this gap, it is crucial for a machine to perceive and understand the user’s current interaction and affective state, as well as it is necessary to register the user’s social signals, which are composed of dynamic multimodal behavioral cues. Building intelligent artificial agents or companions capable to interact with humans in the same way humans interact with each other is a major challenge in HMI. The TC09 on Pattern Recognition in Human-Machine-Interaction mainly focuses on pattern recognition, machine learning and information fusion methods for the perception of the user’s affective state, activities and intentions.
Research topics of TC 09 include but are not limited:
Pattern Recognition and Machine Learning Algorithms to recognize emotions, activities and intentions
- Learning from unlabeled and partially labeled data
- Learning with noisy labels
- Deep learning architectures
- Learning of time series
Algorithms to combine information from multiple modalities
- Information fusion (early, late, intermediate fusion)
- Multi Classifier Systems and Multi View Classifiers
- Temporal information fusion
- Dealing with Uncertainty
Applications of HMI
- Intelligent interaction
- Assistive systems
- Companion systems
- Robotics