3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 13240
- Type
- E - Conference contribution
- DOI
-
10.1007/978-3-319-27677-9_13
- Title of conference / published proceedings
- Pattern Recognition: Applications and Methods. ICPRAM 2015. Lecture Notes in Computer Science
- First page
- 199
- Volume
- 9493
- Issue
- -
- ISSN
- 0302-9743
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2016
- 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
-
2
- Research group(s)
-
H - Computer Vision and Machine Learning Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The underpinning research for this LNCS paper was originally published at the International Conference on Pattern Recognition Applications and Methods (ICPRAM 2015, Portugal). That conference paper was awarded the Best Paper Award and invited, in a significantly extended form, for publication in the LNCS. This extended version fully details a new approach for representing 3D face scans using geodesic-distance measurements between landmarks. It describes the first use of a newly designed geodesic-map for recognition of 3D faces. The paper was instrumental in developing methods for face analysis to aid assessment of cardiometabolic risk factors in the FP7 Funded SEMEOTICONS project.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
