Robustly classifying facial components using a set of adjusted pixel features

Matthias Wimmer, Christoph Mayer, Bernd Radig

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Efficient and accurate localization of the components of human faces, such as skin, lips, eyes, and brows, provides benefit to various real-world applications. However, high intra-class and small inter-class variations in color prevent simple but quick pixel classifiers from yielding robust results. In contrast, more elaborate classifiers consider shape or region features but they do not achieve real-time performance. In this paper, we show that it definitely is possible to robustly determine the facial components and achieve far more than real-time performance. We also use quick pixellevel classifiers and provide them with a set of pixel features that are adapted to the image characteristics beforehand. We do not manually select the pixel features and specify the calculation rules. In contrast, our idea is to provide a multitude of features and let the Machine Learning algorithm decide which of them are important. The evaluation draws a comparison to fixed approaches that do not adapt the computation of the features to the image content in any way. The obtained accuracy is precise enough to be used for real-world applications such as for model-based interpretation of human faces.

Original languageEnglish
Title of host publication2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
DOIs
StatePublished - 2008
Event2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 - Amsterdam, Netherlands
Duration: 17 Sep 200819 Sep 2008

Publication series

Name2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008

Conference

Conference2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
Country/TerritoryNetherlands
CityAmsterdam
Period17/09/0819/09/08

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