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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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Published on: December 3, 2013

Inverse rendering of faces with a 3D morphable model.

Oswald Aldrian1, William A P Smith

  • 1Department of Computer Science, University of York, York, United Kingdom. oa525@york.ac.uk

IEEE Transactions on Pattern Analysis and Machine Intelligence
|March 23, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a 3D Morphable Model (3DMM) framework for inverse face rendering. It accurately recovers 3D shape, texture, and lighting from single images, outperforming existing methods.

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Area of Science:

  • Computer Vision
  • Computer Graphics
  • Machine Learning

Background:

  • Accurate 3D face reconstruction from images is crucial for various applications.
  • Existing methods often struggle with complex lighting and texture variations.

Purpose of the Study:

  • To present a comprehensive framework for inverse rendering of faces using a 3D Morphable Model (3DMM).
  • To develop accurate and efficient methods for recovering 3D shape, texture, lighting, and camera parameters from single images.

Main Methods:

  • Decomposition of image formation into geometric and photometric components.
  • Formulation of the problem as a solvable multilinear system.
  • Novel algorithm for 3D shape recovery incorporating generalization error.
  • Two linear methods for recovering facial texture, lighting, and reflectance.

Main Results:

  • The proposed framework achieves accurate and efficient inverse rendering.
  • The objective function is convex, guaranteeing a global solution.
  • Outperformed a state-of-the-art algorithm on a public database.
  • Demonstrated successful application in a face recognition experiment.

Conclusions:

  • The developed framework provides a robust solution for 3D face inverse rendering.
  • The method's ability to recover detailed facial properties enhances downstream applications like recognition.
  • This work advances the state-of-the-art in 3D face reconstruction and analysis.