A Validated Method for Dense Non-rigid 3D Face Registration
Abstract
Deformable surface fitting methods have been widely used to establish dense correspondence across different 3D objects of the same class. Dense correspondence is a critical step in constructing morphable face models for face recognition. In this paper a mainstream method for constructing dense correspondences is evaluated on 912 3D face scans from the Face Recognition Grand Challenge FRGC V1 database. A number of modifications to the standard deformable surface approach are introduced to overcome limitations identified in the evaluation. Proposed modifications include multi-resolution fitting, adaptive correspondence search range and enforcing symmetry constraints. The modified deformable surface approach is validated on the 912 FRGC 3D face scans and is shown to overcome limitations of the standard approach which resulted in gross fitting errors. The modified approach halves the rms fitting error with 98% of points within 0.5mm of their true position compared to 67% with the standard approach.
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- Authors
- Tena, J., Hamouz, M., Hilton, A., & Illingworth, J.
- Affiliations
- University of Surrey (GB)
- ORCID
- Hilton, Adrian
- Venue
- 2006 IEEE International Conference on Video and Signal Based Surveillance
- Publisher
- IEEE
- Published
- 2006-11
- Pages
- 81-81
- OpenAlex
- W2093510936
- Cited by
- 32
- References
- 18
- Citations by year
- 2025: 1 · 2024: 1 · 2021: 2 · 2020: 1 · 2018: 2 · 2016: 3 · 2014: 2 · 2013: 3 · 2012: 2
- FWCI
- 3.68
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (publishedVersion)
- Open Research (University of Surrey) (submittedVersion)
- Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
- Funders
- Engineering and Physical Sciences Research Council
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- 3D face registration, dense correspondence, morphable face model, face recognition, symmetry constraints, 3D face scans
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