3D AAM based face alignment under wide angular variations using 2D and 3D data

Hao Hsueh Wang*, Andreas Dopfer, Chieh-Chih Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Active Appearance Models (AAMs) are widely used to estimate the shape of the face together with its orientation, but AAM approaches tend to fail when the face is under wide angular variations. Although it is feasible to capture the overall 3D face structure using 3D data from range cameras, the locations of facial features are often estimated imprecisely or incorrectly due to depth measurement uncertainty. Face alignment using 2D and 3D images suffer from different issues and have varying reliability in different situations. The existing approaches introduce a weighting function to balance 2D and 3D alignments in which the weighting function is tuned manually and the sensor characteristics are not taken into account. In this paper, we propose to balance 3D face alignment using 2D and 3D data based on the observed data and the sensors characteristics. The feasibility of wide-angle face alignment is demonstrated using two different sets of depth and conventional cameras. The experimental results show that a stable alignment is achieved with a maximum improvement of 26% compared to 3D AAM using 2D image and 30% improvement over the state-of-the-art 3DMM methods in terms of 3D head pose estimation.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4450-4455
Number of pages6
ISBN (Print)9781467314039
DOIs
StatePublished - 1 Jan 2012
Event 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 - Saint Paul, MN, United States
Duration: 14 May 201218 May 2012

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
CountryUnited States
CitySaint Paul, MN
Period14/05/1218/05/12

Fingerprint Dive into the research topics of '3D AAM based face alignment under wide angular variations using 2D and 3D data'. Together they form a unique fingerprint.

  • Cite this

    Wang, H. H., Dopfer, A., & Wang, C-C. (2012). 3D AAM based face alignment under wide angular variations using 2D and 3D data. In 2012 IEEE International Conference on Robotics and Automation, ICRA 2012 (pp. 4450-4455). [6224590] (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2012.6224590