Publication
2D-to-3D facial expression transfer
Conference Article
Conference
International Conference on Pattern Recognition (ICPR)
Edition
24th
Pages
2008-2013
Doc link
https://doi.org/10.1109/ICPR.2018.8545228
File
Authors
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Rotger Moll, Gemma
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Lumbreras Ruiz, Felipe
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Moreno Noguer, Francesc
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Agudo Martínez, Antonio
Projects associated
Abstract
Automatically changing the expression and physical features of a face from an input image is a topic that has been traditionally tackled in a 2D domain. In this paper, we bring this problem to 3D and propose a framework that given an input RGB video of a human face under a neutral expression, initially computes his/her 3D shape and then performs a transfer to a new and potentially non-observed expression. For this purpose, we parameterize the rest shape --obtained from standard factorization approaches over the input video-- using a triangular mesh which is further clustered into larger macro-segments. The expression transfer problem is then posed as a direct mapping between this shape and a source shape, such as the blend shapes of an off-the-shelf 3D dataset of human facial expressions. The mapping is resolved to be geometrically consistent between 3D models by requiring points in specific regions to map on semantic equivalent regions. We validate the approach on several synthetic and real examples of input faces that largely differ from the source shapes, yielding very realistic expression transfers even in cases with topology changes, such as a synthetic video sequence of a single-eyed cyclops.
Categories
computer vision, optimisation.
Author keywords
Facial Expression Transfer
Scientific reference
G. Rotger, F. Lumbreras, F. Moreno-Noguer and A. Agudo. 2D-to-3D facial expression transfer, 24th International Conference on Pattern Recognition, 2018, Beijing, China, pp. 2008-2013.
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