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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2020.2986496
|2 doi
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|a eng
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| 100 |
1 |
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|a Grasshof, Stella
|e verfasserin
|4 aut
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| 245 |
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|a Multilinear Modelling of Faces and Expressions
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|c 2021
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|a Text
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|a Date Completed 10.12.2021
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|a Date Revised 14.12.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a In this work, we present a new versatile 3D multilinear statistical face model, based on a tensor factorisation of 3D face scans, that decomposes the shapes into person and expression subspaces. Investigation of the expression subspace reveals an inherent low-dimensional substructure, and further, a star-shaped structure. This is due to two novel findings. (1) Increasing the strength of one emotion approximately forms a linear trajectory in the subspace. (2) All these trajectories intersect at a single point - not at the neutral expression as assumed by almost all prior works-but at an apathetic expression. We utilise these structural findings by reparameterising the expression subspace by the fourth-order moment tensor centred at the point of apathy. We propose a 3D face reconstruction method from single or multiple 2D projections by assuming an uncalibrated projective camera model. The non-linearity caused by the perspective projection can be neatly included into the model. The proposed algorithm separates person and expression subspaces convincingly, and enables flexible, natural modelling of expressions for a wide variety of human faces. Applying the method on independent faces showed that morphing between different persons and expressions can be performed without strong deformations
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Ackermann, Hanno
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Brandt, Sami Sebastian
|e verfasserin
|4 aut
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| 700 |
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|a Ostermann, Jorn
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 43(2021), 10 vom: 30. Okt., Seite 3540-3554
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|g volume:43
|g year:2021
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|g day:30
|g month:10
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|u http://dx.doi.org/10.1109/TPAMI.2020.2986496
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