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Matthias Wimmer, Christoph Mayer, and Bernd Radig. Recognizing Facial Expressions Using Model-based Image Interpretation. In Verbal and Nonverbal Communication Behaviours, COST Action 2102 International Workshop, , Vietri sul Mare, Italy, April 2008. Invited Paper
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Abstract
Even if electronic devices widely occupy our daily lives, human-machine interaction still lacks intuition. Therefore, researchers intend to resolve these shortcomings by augmenting traditional systems with aspects of human-human interaction and consider human emotion, behavior, and intention. This publication focusses on one aspect of this challenge: recognizing facial expressions. Our approach achieves real-time performance and provides robustness for real-world applicability. This computer vision task comprises of various phases for which it exploits model-based techniques that accurately localize facial features, seamlessly track them through image sequences, and finally infer facial expressions visible. We specifically adapt state-of-the-art techniques to each of these challenging phases. Our system has been successfully presented to industrial, political, and scientific audience in various events.
BibTeX Entry
@inproceedings{ wimmer08recognizing,
author = {Matthias Wimmer and Christoph Mayer and Bernd Radig},
title = {Recognizing Facial Expressions Using Model-based Image Interpretation},
booktitle = {Verbal and Nonverbal Communication Behaviours, COST Action 2102 International Workshop},
year = {2008},
month = {April},
address = {Vietri sul Mare, Italy},
publisher = {},
xxxvolume = {},
xxxpages = {},
bib2html_pubtype = {Refereed Workshop Paper},
bib2html_rescat = {Image Understanding},
bib2html_groups = {IU},
abstract =
{Even if electronic devices widely occupy our daily lives, human-machine interaction still lacks intuition. Therefore, researchers intend to resolve these shortcomings by augmenting traditional systems with aspects of human-human interaction and consider human emotion, behavior, and intention.
This publication focusses on one aspect of this challenge: recognizing facial expressions. Our approach achieves real-time performance and provides robustness for real-world applicability. This computer vision task comprises of various phases for which it exploits model-based techniques that accurately localize facial features, seamlessly track them through image sequences, and finally infer facial expressions visible. We specifically adapt state-of-the-art techniques to each of these challenging phases. Our system has been successfully presented to industrial, political, and scientific audience in various events.},
note = {Invited Paper},
}
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