Depth estimation of face images based on the constrained ICA model

Zhan Li Sun, Kin Man Lam

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


In this paper, we propose a novel and 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 proposed algorithm, the rotation and translation process from a frontal-view face image to a non-frontal-view face image is at first formulated as a constrained independent component analysis (cICA) model. Then, the overcomplete ICA problem is converted into a normal ICA problem. The CANDIDE model is also employed to design a reference signal in our algorithm. Moreover, a model-integration method is proposed to improve the depth-estimation accuracy when multiple non-frontal-view face images are available. Experimental results on a real 3D face image database demonstrate the feasibility and efficiency of the proposed method.
Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing, PCM 2010 - 11th Pacific Rim Conference on Multimedia, Proceedings
Number of pages10
EditionPART 1
Publication statusPublished - 8 Nov 2010
Event11th Pacific Rim Conference on Multimedia, PCM 2010 - Shanghai, China
Duration: 21 Sep 201024 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6297 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th Pacific Rim Conference on Multimedia, PCM 2010

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this