Score Level Fusion of Ear and Face Local 3D Features for Fast and Expression-Invariant Human Recognition

S.M.S. Islam, Mohammed Bennamoun, Ajmal Mian, Rowan Davies

    Research output: Chapter in Book/Conference paperConference paper

    14 Citations (Scopus)

    Abstract

    Increasing risks of spoof attacks and other common problems of unimodal biometric systems such as intra-class variations, non-universality and noisy data necessitate the use of multimodal biometrics. The face and the ear are highly attractive biometric traits for combination because of their physiological structure and location. Besides, both of them can be acquired non-intrusively. However, changes of facial expressions, variations in pose, scale and illumination and the presence of hair and ornaments present some genuine challenges. In this paper, a 3D local feature based approach is proposed to fuse ear and face biometrics at the score level. Experiments with FRGC v.2 and the University of Notre Dame Biometric databases show that the technique achieves an identification rate of 98.71% and a verification rate of 99.68% (at 0.001 FAR) for fusion of the ear with neutral face biometrics. It is also found to be fast and robust to facial expressions achieving 98.1% and 96.83% identification and verification rates respectively.
    Original languageEnglish
    Title of host publicationImage Analysis and Recognition, Proceedings
    EditorsM. Kamel, A. Campilho
    Place of PublicationBerlin Heidelberg, Germany
    PublisherSpringer
    Pages387-396
    Volume5627
    ISBN (Print)03029743
    DOIs
    Publication statusPublished - 2009
    EventScore Level Fusion of Ear and Face Local 3D Features for Fast and Expression-Invariant Human Recognition - Halifax, Canada
    Duration: 1 Jan 2009 → …

    Conference

    ConferenceScore Level Fusion of Ear and Face Local 3D Features for Fast and Expression-Invariant Human Recognition
    Period1/01/09 → …

    Fingerprint Dive into the research topics of 'Score Level Fusion of Ear and Face Local 3D Features for Fast and Expression-Invariant Human Recognition'. Together they form a unique fingerprint.

    Cite this