3D shape and pose estimation of face images using the nonlinear least-squares model

Zhan Li Sun, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose an efficient algorithm to reconstruct the 3D structure of a human face from one or a number of its 2D images with different poses. In our algorithm, the nonlinear least-squares model is employed to estimate the 3D structure of the face and the respective poses of the 2D face images concerned by means of the similarity transform. Furthermore, different optimization schemes are presented with regard to the accuracy levels and the training time required. Our algorithm also embeds the symmetrical property of human faces and the regularization term based on linear correlation into the optimization procedure so as to alleviate the sensitivities arising from changes in poses and improve the estimation accuracy of the 3D structure. Experimental results demonstrate the feasibility and efficiency of the proposed methods.
Original languageEnglish
Title of host publicationAPSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
Pages895-898
Number of pages4
Publication statusPublished - 1 Dec 2010
Event2nd Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2010 - Biopolis, Singapore
Duration: 14 Dec 201017 Dec 2010

Conference

Conference2nd Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2010
CountrySingapore
CityBiopolis
Period14/12/1017/12/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this