Facial feature detection using distance vector fields

Stylianos Asteriadis, Nikos Nikolaidis, Ioannis Pitas

Research output: Contribution to journalArticleAcademicpeer-review

50 Citations (Scopus)

Abstract

A novel method for eye and mouth detection and eye center and mouth corner localization, based on geometrical information is presented in this paper. First, a face detector is applied to detect the facial region, and the edge map of this region is calculated. The distance vector field of the face is extracted by assigning to every facial image pixel a vector pointing to the closest edge pixel. The x and y components of these vectors are used to detect the eyes and mouth regions. Luminance information is used for eye center localization, after removing unwanted effects, such as specular highlights, whereas the hue channel of the lip area is used for the detection of the mouth corners. The proposed method has been tested on the XM2VTS and BioID databases, with very good results. © 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)1388-1398
Number of pages11
JournalPattern Recognition
Volume42
Issue number7
DOIs
Publication statusPublished - Jul 2009
Externally publishedYes

Keywords

  • Distance map
  • Distance vector field (DVF)
  • Facial features detection

Cite this