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ECCV
2006
Springer

Robust Expression-Invariant Face Recognition from Partially Missing Data

15 years 1 months ago
Robust Expression-Invariant Face Recognition from Partially Missing Data
Abstract. Recent studies on three-dimensional face recognition proposed to model facial expressions as isometries of the facial surface. Based on this model, expression-invariant signatures of the face were constructed by means of approximate isometric embedding into flat spaces. Here, we apply a new method for measuring isometry-invariant similarity between faces by embedding one facial surface into another. We demonstrate that our approach has several significant advantages, one of which is the ability to handle partially missing data. Promising face recognition results are obtained in numerical experiments even when the facial surfaces are severely occluded.
Alexander M. Bronstein, Michael M. Bronstein, Ron
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2006
Where ECCV
Authors Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
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