Automatic eyes and nose detection using curvature analysis

J. Matías Di Martino, Alicia Fernández, José Ferrari

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

Abstract

In the present work we propose a method for detecting the nose and eyes position when we observe a scene that contains a face. The main goal of the proposed technique is that it capable of bypassing the 3D explicit mapping of the face and instead take advantage of the information available in the Depth gradient map of the face. To this end we will introduce a simple false positive rejection approach restricting the distance between the eyes, and between the eyes and the nose. The main idea is to use nose candidates to estimate those regions where is expected to find the eyes, and vice versa. Experiments with Texas database are presented and the proposed approach is testes when data presents different power of noise and when faces are in different positions with respect to the camera.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlvaro Pardo, Josef Kittler
PublisherSpringer Verlag
Pages271-278
Number of pages8
ISBN (Print)9783319257501
DOIs
StatePublished - 2015
Externally publishedYes
Event20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015 - Montevideo, Uruguay
Duration: 9 Nov 201512 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9423
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015
Country/TerritoryUruguay
CityMontevideo
Period9/11/1512/11/15

Keywords

  • Differential 3D reconstruction
  • Eyes detection
  • Landmark detection
  • Nose tip detection

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