Efficient 3D morphable face model fitting
- Submitting institution
-
University of York
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 62777500
- Type
- D - Journal article
- DOI
-
10.1016/j.patcog.2017.02.007
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 366
- Volume
- 67
- Issue
- -
- ISSN
- 0031-3203
- Open access status
- Technical exception
- Month of publication
- February
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
-
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In this paper, we proposed a novel approach to 3D face reconstruction from single images. Our approach consists of an efficient stepwise optimisation strategy, resulting in robust and reliable convergence on unconstrained images. The work has important practical applications ranging from health care, entertainment, to automotive safety. Our work has been recognised both nationally and internationally, e.g. [Liu (Sichuan University, China / MSU, USA), TPAMI 2020], [Egger (MIT, USA), ACM TOG 2020].
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -