3D head pose estimation using range images for face recognition

Hwanjong Song, Kwanghoon Sohn

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

1 Citation (Scopus)

Abstract

This paper describes a robust three-dimensional (3D) head pose estimation method based on face geometry and linear regression model. Given an unknown range image, we extract six invariant facial features based on face curvature characteristics. For estimating the head pose, we estimate the initial head pose using the SVD method, and perform a refinement procedure to compensate for remaining errors for the X and Y axis. To compensate for the Z axis, we orthogonally project feature points onto the Z plane and estimate the face center line based on the linear regression model. Experimental results show that less than a 0.5 degree error on average for each axis has been achieved.

Original languageEnglish
Title of host publication2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Pages1256-1261
Number of pages6
Publication statusPublished - 2004 Dec 1
Event8th International Conference on Control, Automation, Robotics and Vision (ICARCV) - Kunming, China
Duration: 2004 Dec 62004 Dec 9

Publication series

Name2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Volume2

Other

Other8th International Conference on Control, Automation, Robotics and Vision (ICARCV)
CountryChina
CityKunming
Period04/12/604/12/9

Fingerprint

Face recognition
Linear regression
Singular value decomposition
Geometry

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Song, H., & Sohn, K. (2004). 3D head pose estimation using range images for face recognition. In 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV) (pp. 1256-1261). (2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV); Vol. 2).
Song, Hwanjong ; Sohn, Kwanghoon. / 3D head pose estimation using range images for face recognition. 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV). 2004. pp. 1256-1261 (2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)).
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title = "3D head pose estimation using range images for face recognition",
abstract = "This paper describes a robust three-dimensional (3D) head pose estimation method based on face geometry and linear regression model. Given an unknown range image, we extract six invariant facial features based on face curvature characteristics. For estimating the head pose, we estimate the initial head pose using the SVD method, and perform a refinement procedure to compensate for remaining errors for the X and Y axis. To compensate for the Z axis, we orthogonally project feature points onto the Z plane and estimate the face center line based on the linear regression model. Experimental results show that less than a 0.5 degree error on average for each axis has been achieved.",
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Song, H & Sohn, K 2004, 3D head pose estimation using range images for face recognition. in 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV). 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV), vol. 2, pp. 1256-1261, 8th International Conference on Control, Automation, Robotics and Vision (ICARCV), Kunming, China, 04/12/6.

3D head pose estimation using range images for face recognition. / Song, Hwanjong; Sohn, Kwanghoon.

2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV). 2004. p. 1256-1261 (2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV); Vol. 2).

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

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N2 - This paper describes a robust three-dimensional (3D) head pose estimation method based on face geometry and linear regression model. Given an unknown range image, we extract six invariant facial features based on face curvature characteristics. For estimating the head pose, we estimate the initial head pose using the SVD method, and perform a refinement procedure to compensate for remaining errors for the X and Y axis. To compensate for the Z axis, we orthogonally project feature points onto the Z plane and estimate the face center line based on the linear regression model. Experimental results show that less than a 0.5 degree error on average for each axis has been achieved.

AB - This paper describes a robust three-dimensional (3D) head pose estimation method based on face geometry and linear regression model. Given an unknown range image, we extract six invariant facial features based on face curvature characteristics. For estimating the head pose, we estimate the initial head pose using the SVD method, and perform a refinement procedure to compensate for remaining errors for the X and Y axis. To compensate for the Z axis, we orthogonally project feature points onto the Z plane and estimate the face center line based on the linear regression model. Experimental results show that less than a 0.5 degree error on average for each axis has been achieved.

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Song H, Sohn K. 3D head pose estimation using range images for face recognition. In 2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV). 2004. p. 1256-1261. (2004 8th International Conference on Control, Automation, Robotics and Vision (ICARCV)).