Output details
11 - Computer Science and Informatics
University of York
Article title
A Machine-Learning Approach to Keypoint Detection and Landmarking on 3D Meshes
Type
D - Journal article
Title of journal
International Journal of Computer Vision
Article number
-
Volume number
102
Issue number
1-3
First page of article
146
ISSN of journal
0920-5691
Year of publication
2012
Number of additional authors
2
Additional information
<23>Many applications in medical imaging, biometric security and entertainment require comprehensive knowledge of 3D shape. This requires the fitting of a dense shape model to a 3D object scan that is automatically initialised with the fitting of a sparse model. This work is the first that employs generic machine learning techniques that allow a sparse model to be fitted to a 3D face scan, which may be in any pose and partially occluded. This work (along with another paper) led to a 1-year Royal Academy of Engineering - Leverhulme Trust Senior Research Fellowship for Nick Pears.
Interdisciplinary
-
Cross-referral requested
-
Research group
E - Advanced Computer Architectures
Citation count
0
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
