Face Tracking and Pose Estimation Using Affine Motion Parameters

Yao Pingping, G Evans, A Calway

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. The technique is based on an affine approximation to the motion of projected facial features such as eyes, mouth and nose. Tracking stability is maintained by enforcing the affine relationship amongst the motion of the features using linear regression and application of a Kalman filter to the estimated affine parameters. Facial pose is estimated using an ellipse-circle correspondence technique based on the affine transformation between the features in the current view and those in a fronto-parallel view. The method has the advantage of being simple to implement and not relying on assumed facial characteristics. Experiments on both synthetic and real sequences illustrate the effectiveness of the approach.
Translated title of the contributionFace Tracking and Pose Estimation Using Affine Motion Parameters
Original languageEnglish
Title of host publicationUnknown
EditorsI Austvoll
PublisherNorwegian Society for Image Processing and Pattern Recognition
Pages531 - 536
Number of pages5
ISBN (Print)8299594006
Publication statusPublished - Jun 2001

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 12th Scandinavian Conference on Image Analysis


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