Facial Component Detection in Thermal Imagery

Brais Martinez, Xavier Binefa, Maja Pantic

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

    27 Citations (Scopus)
    150 Downloads (Pure)


    This paper studies the problem of detecting facial components in thermal imagery (specifically eyes, nostrils and mouth). One of the immediate goals is to enable the automatic registration of facial thermal images. The detection of eyes and nostrils is performed using Haar features and the GentleBoost algorithm, which are shown to provide superior detection rates. The detection of the mouth is based on the detections of the eyes and the nostrils and is performed using measures of entropy and self similarity. The results show that reliable facial component detection is feasible using this methodology, getting a correct detection rate for both eyes and nostrils of 0.8. A correct eyes and nostrils detection enables a correct detection of the mouth in 65% of closed-mouth test images and in 73% of open-mouth test images.
    Original languageUndefined
    Title of host publicationIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010, Workshop on Object Tracking & Classification Beyond and in the Visible Spectrum
    Place of PublicationUSA
    Number of pages7
    ISBN (Print)978-1-4244-7029-7
    Publication statusPublished - 14 Jun 2010
    Event23rd IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, United States
    Duration: 13 Jun 201018 Jun 2010
    Conference number: 23

    Publication series

    PublisherIEEE Computer Society


    Workshop23rd IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010
    Abbreviated titleCVPR 2010
    Country/TerritoryUnited States
    CitySan Francisco


    • METIS-276369
    • EWI-19562
    • IR-75977

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