Probabilistic Facial Feature Extraction Using Joint Distribution of Location and Texture Information

Authors:
Mustafa Berkay Yilmaz;Hakan Erdogan;Mustafa Unel
Affiliations:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey;Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey;Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Year:
2009

Citing 3
Cited 1

Adaptive Automatic Facial Feature Segmentation

FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Active Appearance Models Revisited

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FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition

Facial feature extraction using a probabilistic approach

Image Communication

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Abstract

In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn feature information from training data. It finds the best facial feature locations by maximizing the joint distribution of location and texture parameters. We first introduce an independence assumption. Then, we improve upon this model by assuming dependence of location parameters but independence of texture parameters. We model combined location parameters with a multivariate Gaussian for computational reasons. The texture parameters are modeled with a Gaussian mixture model. It is shown that the new method outperforms active appearance models for the same experimental setup.