USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE

Yao Pingping; G Evans; A Calway

USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE

Yao Pingping
, G Evans
, A Calway

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

40 Citations (Scopus)

Abstract

We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. It 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 a Kalman filter. 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.

Translated title of the contribution	USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE
Original language	English
Title of host publication	Unknown
Editors	I. Pitas
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	919 - 922
Number of pages	3
ISBN (Print)	0780367278
Publication status	Published - Oct 2001

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the IEEE International Conference on Image Processing

Access to Document

http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=1000590

Handle.net

Persistent link

Cite this

@inproceedings{af9ef97f7082418f9434ccb9ed9a1e7b,

title = "USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE",

abstract = "We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. It 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 a Kalman filter. 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.",

author = "Yao Pingping and G Evans and A Calway",

note = "Conference Proceedings/Title of Journal: Proceedings of the IEEE International Conference on Image Processing",

year = "2001",

month = oct,

language = "English",

isbn = "0780367278",

pages = "919 -- 922",

editor = "I. Pitas",

booktitle = "Unknown",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

TY - GEN

T1 - USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE

AU - Pingping, Yao

AU - Evans, G

AU - Calway, A

N1 - Conference Proceedings/Title of Journal: Proceedings of the IEEE International Conference on Image Processing

PY - 2001/10

Y1 - 2001/10

N2 - We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. It 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 a Kalman filter. 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.

AB - We describe a method for tracking a person's face through an image sequence and estimating the 3-D facial pose within each frame. It 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 a Kalman filter. 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.

M3 - Conference Contribution (Conference Proceeding)

SN - 0780367278

SP - 919

EP - 922

BT - Unknown

A2 - Pitas, I.

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

USING AFFINE CORRESPONDENCE TO ESTIMATE 3-D FACIAL POSE

Abstract

Bibliographical note

Access to Document

Handle.net

Fingerprint

Cite this