Locating facial features and pose estimation using a 3D shape model

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


We present an automatic method for locating facial features and estimating head pose in 2D images and video using a 3D shape model and local view-based texture patches. After automatic initialization, the 3D pose and shape are refined iteratively to optimize the match between the appearance predicted by the model, and the image. The local texture patches are generated using the current 3D pose and shape, and the locations of model points are refined by neighbourhood search, using normalized cross-correlation to provide some robustness to illumination. A key aspect is the presentation of a large-scale quantitative evaluation, comparing the method to a well-established 2D approach. We show that the accuracy of feature location for the 3D system is comparable to that of the 2D system for near-frontal faces, but significantly better for sequences which involve large rotations, obtaining estimates of pose to within 10° at headings of up to 70°. © 2009 Springer-Verlag.

Bibliographical metadata

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
PublisherSpringer Nature
Number of pages11
ISBN (Print)3642103308, 9783642103308
Publication statusPublished - 2009
Event5th International Symposium on Advances in Visual Computing, ISVC 2009 - Las Vegas, NV
Event duration: 1 Jul 2009 → …


Conference5th International Symposium on Advances in Visual Computing, ISVC 2009
CityLas Vegas, NV
Period1/07/09 → …