Fully Automated and Highly Accurate Dense Correspondence for Facial Surfaces

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9914)

Abstract

We present a novel framework for fully automated and highly accurate determination of facial landmarks and dense correspondence, e.g. a topologically identical mesh of arbitrary resolution, across the entire surface of 3D face models. For robustness and reliability of the proposed approach, we are combining 2D landmark detectors and 3D statistical shape priors with a variational matching method. Instead of matching faces in the spatial domain only, we employ image registration to align the 2D parametrization of the facial surface to a planar template we call the Unified Facial Parameter Domain (ufpd). This allows us to simultaneously match salient photometric and geometric facial features using robust image similarity measures while reasonably constraining geometric distortion in regions with less significant features. We demonstrate the accuracy of the dense correspondence established by our framework on the BU3DFE database with 2500 facial surfaces and show, that our framework outperforms current state-of-the-art methods with respect to the fully automated location of facial landmarks.

Keywords

Dense face matching Face shape and appearance models Markerless motion capture 

Supplementary material

434776_1_En_38_MOESM1_ESM.pdf (9 mb)
Supplementary material 1 (pdf 9165 KB)

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Mathematics for Life and Materials SciencesZuse Institute BerlinBerlinGermany

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