Facial occlusion reconstruction: Recovering both the global structure and the local detailed texture components

Ching Ting Tu, Jeim Jier James Lien

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

7 Citations (Scopus)

Abstract

An automatic facial occlusion reconstruction system based upon a novel learning algorithm called the direct combined model (DCM) approach is presented. The system comprises two basic DCM modules, namely a shape reconstruction module and a texture reconstruction module. Each module models the occluded and non-occluded regions of the facial image in a single, combined eigenspace, thus preserving the correlations between the geometry of the facial features and the pixel grayvalues, respectively, in the two regions. As a result, when shape or texture information is available only for the non-occluded region of the facial image, the optimal shape and texture of the occluded region can be reconstructed via a process of Bayesian inference within the respective eigenspaces. To enhance the quality of the reconstructed results, the shape reconstruction module is rendered robust to facial feature point labeling errors by suppressing the effects of biased noises. Furthermore, the texture reconstruction module recovers the texture of the occluded facial image by synthesizing the global texture image and the local detailed texture image. The experimental results demonstrate that compared to existing facial reconstruction systems, the reconstruction results obtained using the proposed DCM-based scheme are quantitatively closer to the ground truth.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
PublisherSpringer Verlag
Pages141-151
Number of pages11
ISBN (Print)9783540771289
DOIs
Publication statusPublished - 2007
Event2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007 - Santiago, Chile
Duration: 2007 Dec 172007 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4872 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007
CountryChile
CitySantiago
Period07-12-1707-12-19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Facial occlusion reconstruction: Recovering both the global structure and the local detailed texture components'. Together they form a unique fingerprint.

Cite this