4.8 Article

Towards a Complete 3D Morphable Model of the Human Head

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2020.2991150

关键词

Magnetic heads; Face; Ear; Three-dimensional displays; Shape; Computational modeling; 3DMM; morphable model combination; 3D reconstruction; craniofacial 3DMM

资金

  1. EPSRC [EP/N007743/1, EP/S010203/1]
  2. Google Faculty Award
  3. Google Daydream Award
  4. Royal Academy of Engineering under the Leverhulme Trust Senior Fellowship scheme
  5. EPSRC [EP/S010203/1, EP/N007743/1] Funding Source: UKRI

向作者/读者索取更多资源

The study introduces the most complete 3DMM of the human head to date, which combines existing models of different overlapping head parts to achieve state-of-the-art performance. The new model builds a combined face-and-head shape model that blends the variability and facial detail of an existing face model with the full head modelling capability of an existing head model.
Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: (i). use a regressor to complete missing parts of one model using the other, and (ii). use the Gaussian Process framework to blend covariance matrices from multiple models. Thus, we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color.

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