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A morphable model for the synthesis of 3D faces

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Blanz, Volker, Vetter, Thomas·1999·Proceedings of the 26th annual conference on Computer graphics and interactive techniques - SIGGRAPH '99

Abstract

In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face images or new 3D face models can be registered automatically by computing dense one-to-one correspondence to an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces with an "unlikely" appearance. Starting from an example set of 3D face models, we derive a morphable face model by transforming the shape and texture of the examples into a vector space representation. New faces and expressions can be modeled by forming linear combinations of the prototypes. Shape and texture constraints derived from the statistics of our example faces are used to guide manual modeling or automated matching algorithms. We show 3D face reconstructions from single images and their applications for photo-realistic image manipulations. We also demonstrate face manipulations according to complex parameters such as gender, fullness of a face or its distinctiveness.

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Metadata

Authors
Blanz, V., & Vetter, T.
Venue
Proceedings of the 26th annual conference on Computer graphics and interactive techniques - SIGGRAPH '99
Publisher
ACM Press
Published
1999
Pages
187-194
OpenAlex
W2237250383
Cited by
4,710
References
0
FWCI
51.56
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: A morphable model for the synthesis of 3D faces. https://app.cochat.ai/papers/10.1145/311535.311556
The paper
Blanz, V., & Vetter, T. (1999). A morphable model for the synthesis of 3D faces. Proceedings of the 26th annual conference on Computer graphics and interactive techniques - SIGGRAPH '99. https://doi.org/10.1145/311535.311556

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.