Uniformly spaced 3D modeling of human face from two images using parallel particle swarm optimization

Yau Zen Chang*, Jung Fu Hou, Yi Hsiang Tsao, Shih Tseng Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper proposes a scheme for finding the correspondence between uniformly spaced locations on the images of human face captured from different viewpoints at the same instant. The correspondence is dedicated for 3D reconstruction to be used in the registration procedure for neurosurgery where the exposure to projectors must be seriously restricted. The approach utilizes structured light to enhance patterns on the images and is initialized with the scale-invariant feature transform (SIFT). Successive locations are found according to spatial order using a parallel version of the particle swarm optimization algorithm. Furthermore, false locations are singled out for correction by searching for outliers from fitted curves. Case studies show that the scheme is able to correctly generate 456 evenly spaced 3D coordinate points in 23 seconds from a single shot of projected human face using a PC with 2.66 GHz Intel Q9400 CPU and 4GB RAM.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XXXIV
DOIs
StatePublished - 2011
EventApplications of Digital Image Processing XXXIV - San Diego, CA, United States
Duration: 22 08 201124 08 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8185
ISSN (Print)0277-786X

Conference

ConferenceApplications of Digital Image Processing XXXIV
Country/TerritoryUnited States
CitySan Diego, CA
Period22/08/1124/08/11

Keywords

  • Computer Vision
  • Correspondence
  • Parallel Computation
  • Particle Swarm Optimization
  • Stereopsis

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