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ECCV
2008
Springer

A Generative Shape Regularization Model for Robust Face Alignment

11 years 3 months ago
A Generative Shape Regularization Model for Robust Face Alignment
In this paper, we present a robust face alignment system that is capable of dealing with exaggerating expressions, large occlusions, and a wide variety of image noises. The robustness comes from our shape regularization model, which incorporates constrained nonlinear shape prior, geometric transformation, and likelihood of multiple candidate landmarks in a three-layered generative model. The inference algorithm iteratively examines the best candidate positions and updates face shape and pose. This model can effectively recover sufficient shape details from very noisy observations. We demonstrate the performance of this approach on two public domain databases and a large collection of real-world face photographs.
Leon Gu, Takeo Kanade
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 2008
Where ECCV
Authors Leon Gu, Takeo Kanade
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