Authors:
Gerald Krell
;
Robert Niese
;
Ayoub Al-Hamadi
and
Bernd Michaelis
Affiliation:
Otto von Guericke University Magdeburg, Germany
Keyword(s):
Man-machine communication, Associative deconvolution, Face analysis, Mimics, Emotion recognition.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Registration
;
Informatics in Control, Automation and Robotics
;
Pattern Recognition
;
Signal Processing, Sensors, Systems Modeling and Control
;
Software Engineering
;
Video Analysis
Abstract:
Facial expression is of increasing importance for man-machine communication.
It is expected that future human computer interaction systems even include emotions of the user.
In this work we present an associative approach based on a multi-channel deconvolution for processing of face expression data derived from video sequences supported by a 3-D facial model generated with stereo support.
Photogrammetric techniques are applied to determine real world geometric measures and to create a feature vector.
Standard classification is used to discriminate between a limited number of mimics, but often fails at transitions from one detected emotion state to another.
The proposed associative approach reduces ambiguities at the transitions between different classified emotions.
This way, typical patterns of facial expression change is considered.