ICPR 2014 Satellite Workshop

Multimodal pattern recognition for social signal processing in human computer interaction

MPRSS 2014, Stockholm (Sweden), August 24, 2014



http://neuro.informatik.uni-ulm.de/MPRSS2014/


MPRSS 2014 mainly focuses on pattern recognition, machine learning and information fusion methods
for the perception of the user’s affective state, activities and intentions. 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 research. Such a type of interactive companion must be capable
of perceiving and interpreting information about the user in order to be able to produce an appropriate response.


The workshop topics include but are not limited to:

A. 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

B. 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

C. Applications relevant to the workshop

· Intelligent interaction

· Assistive systems and companion systems

· Applications, e.g. in healthcare or elderly care

D. Datasets and benchmarks relevant to the workshop topics


Workshop proceedings will be published as postconference procedeedings as Springer LNAI volume.


Important dates

June 30, 2014 Second Round Submission deadline
July 20, 2014 Notification of acceptance
August 24, 2014 Workshop
September 15, 2014 Camera ready version for Springer proceedings


Workshop Organizers

Friedhelm Schwenker (contact)
University of Ulm, Germany
friedhelm.schwenker@uni-ulm.de

Stefan Scherer
University of Southern California
scherer@ict.usc.edu

Louis-Philippe Morency
University of Southern California
morency@ict.usc.edu