Research Output

Feature-preserving detailed 3D face reconstruction from a single image

  Dense 3D face reconstruction plays a fundamental role in visual media production involving digital actors. We improve upon high fidelity reconstruction from a single 2D photo with a reconstruction framework that is robust to large variations in expressions, poses and illumination. We provide a global optimization step improving the alignment of 3D facial geometry to tracked 2D landmarks with 3D Laplacian deformation. Face detail is improved through, extending Shape from Shading reconstruction with fitted albedo prior masks, together with a fast proportionality constraint between depth and image gradients consistent with local self-occlusion behavior. Together these measures better preserve the crucial facial features that define an actor's identity, and we illustrate this through a variety of comparisons with related works.

  • Date:

    13 December 2018

  • Publication Status:

    Published

  • Publisher

    ACM Press

  • DOI:

    10.1145/3278471.3278473

  • Library of Congress:

    QA76 Computer software

  • Dewey Decimal Classification:

    006.6 Computer graphics

  • Funders:

    Edinburgh Napier Funded

Citation

Li, Y., Ma, L., Fan, H., & Mitchell, K. (2018). Feature-preserving detailed 3D face reconstruction from a single image. In CVMP '18 Proceedings of the 15th ACM SIGGRAPH European Conference on Visual Media Productiondoi:10.1145/3278471.3278473

Authors

Keywords

Feature-Preserving, 3D Face Reconstruction, Optimization

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