Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

A quantitative assessment of 3D facial key point localization fitting 2D shape models to curvature information

Sukno, Federico M. orcid logoORCID: 0000-0002-2029-1576, Chowdhury, Tarik A., Waddington, John L. and Whelan, Paul F. orcid logoORCID: 0000-0001-9230-7656 (2011) A quantitative assessment of 3D facial key point localization fitting 2D shape models to curvature information. In: Proceedings of the Irish Machine Vision and Image Processing (IMVIP) Conference, 8-9th Sept 2011.

This work addresses the localization of 11 prominent facial landmarks in 3D by fitting state of the art shape models to 2D data. Quantitative results are provided for 34 scans at high resolution (texture maps of 10 M-pixels) in terms of accuracy (with respect to manual measurements) and precision (repeatability on different images from the same individual). We obtain an average accuracy of approximately 3 mm, and median repeatability of inter-landmark distances typically below 2 mm, which are values comparable to current algorithms on automatic localization of facial landmarks. We also show that, in our experiments, the replacement of texture information by curvature features produced little change in performance, which is an important finding as it suggests the applicability of the method to any type of 3D data.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:computer vision; image analysis; localization; facial landmarks; 3D
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Copyright Information:© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:18598
Deposited On:13 Aug 2013 13:10 by Mark Sweeney . Last Modified 11 Jan 2019 13:07

Full text available as:

[thumbnail of whelan_2011_28.1.pdf]
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader


Downloads per month over past year

Archive Staff Only: edit this record