Thermal face recognition using local interest points and descriptors for HRI applications

Gabriel Hermosilla, Patricio Loncomilla, Javier Ruiz-Del-Solar

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

9 Scopus citations

Abstract

In this article a robust thermal face recognition methodology based on the use of local interest points and descriptors, is proposed. The methodology consists of the following stages: face segmentation, vascular network detection, wide baseline matching using local interest points and descriptors, and classification. The main contribution of this work is the use of a standard wide baseline matching methodology for the comparison of vascular networks from thermal face images. The proposed methodology is validated using a database of thermal images. This work could be of high interest for HRI applications related with the visual recognition of humans, as the ones included in the RoboCup @Home league, because the use of thermal images may overcome limitations such as dependency on illumination conditions and facial expressions.

Original languageEnglish
Title of host publicationRoboCup 2010
Subtitle of host publicationRobot Soccer World Cup XIV
Pages25-35
Number of pages11
DOIs
StatePublished - 2011
Externally publishedYes
Event14th Annual RoboCup International Symposium - Singapore, Singapore
Duration: 25 Jun 201025 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6556 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Annual RoboCup International Symposium
Country/TerritorySingapore
CitySingapore
Period25/06/1025/06/10

Keywords

  • Blood Vessels Matching
  • Face Recognition
  • RoboCup @Home
  • SIFT Matching
  • Thermal Images

Fingerprint

Dive into the research topics of 'Thermal face recognition using local interest points and descriptors for HRI applications'. Together they form a unique fingerprint.

Cite this