Dai, Hang, Pears, Nicholas Edwin orcid.org/0000-0001-9513-5634, Smith, William Alfred Peter orcid.org/0000-0002-6047-0413 et al. (1 more author) (2017) A 3D Morphable Model of Craniofacial Shape and Texture Variation. In: Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017. Title Proceedings / IEEE International Conference on Computer Vision. . , pp. 3104-3112.
Abstract
We present a fully automatic pipeline to train 3D Mor- phable Models (3DMMs), with contributions in pose nor- malisation, dense correspondence using both shape and texture information, and high quality, high resolution tex- ture mapping. We propose a dense correspondence system, combining a hierarchical parts-based template morphing framework in the shape channel and a refining optical flow in the texture channel. The texture map is generated us- ing raw texture images from five views. We employ a pixel- embedding method to maintain the texture map at the same high resolution as the raw texture images, rather than us- ing per-vertex color maps. The high quality texture map is then used for statistical texture modelling. The Headspace dataset used for training includes demographic information about each subject, allowing for the construction of both global 3DMMs and models tailored for specific gender and age groups. We build both global craniofacial 3DMMs and demographic sub-population 3DMMs from more than 1200 distinct identities. To our knowledge, we present the first public 3DMM of the full human head in both shape and texture: the Liverpool-York Head Model. Furthermore, we analyse the 3DMMs in terms of a range of performance metrics. Our evaluations reveal that the training pipeline constructs state-of-the-art models.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017, IEEE. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Keywords: | 3D Morphabe Model; 3D shape registration; 3D imaging |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 28 Aug 2018 12:50 |
Last Modified: | 21 Jan 2025 18:24 |
Published Version: | https://doi.org/10.1109/ICCV.2017.335 |
Status: | Published |
Series Name: | Title Proceedings / IEEE International Conference on Computer Vision. |
Identification Number: | 10.1109/ICCV.2017.335 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135062 |