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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Facial Shape Spaces from Surface Normals
verfasst von : Simone Ceolin, William A. P. Smith, Edwin Hancock
Erschienen in: Image Analysis and Recognition
Verlag: Springer Berlin Heidelberg
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In this paper, we draw on ideas from the field of statistical shape analysis to construct shape-spaces that span facial expressions and gender, and use the resulting shape-model to perform face recognition under varying expression and gender. Our novel contribution is to show how to construct shape-spaces over fields of surface normals rather than Cartesian landmark points. According to this model face needle-maps (or fields of surface normals) are points in a high-dimensional manifold referred to as a shape-space. We compute geodesic distances to compare the similarity between faces and gender difference.