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Robust Expression-Invariant Face Recognition from Partially Missing Data

2020-03-27 | |  66 |   44 |   0

Abstract.
Recent studies on three-dimensional face recognition pro- posed to model facial expressions as isometries of the facial surface. Based on this model, expression-invariant signatures of the face were con- structed 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 demon- strate that our approach has several significant advantages, one of which is the ability to handle partially missing data. Promising face recogni- tion results are obtained in numerical experiments even when the facial surfaces are severely occluded.

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