Personal identification by multiresolution analysis of lifting dyadic wavelets

Shigeru Takan, Koichi Niijima, Koichi Kuzume

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    This paper proposes a novel method for identifying persons by multiresolution analysis of lifting dyadic wavelets. Our method consists of three procedures: face learning, detection and identification. In the learning procedure, new highpass filters for capturing facial parts are constructed by tuning free parameters in the lifting scheme. By using the learned filters, human faces can be detected from each of video frames. A person whose face is detected in a maximum number of frames is identified as a target person. Experimental results show that our personal identification algorithm is fast and accurate.

    Original languageEnglish
    Title of host publication2004 12th European Signal Processing Conference, EUSIPCO 2004
    PublisherEuropean Signal Processing Conference, EUSIPCO
    Pages2283-2286
    Number of pages4
    ISBN (Electronic)9783200001657
    Publication statusPublished - Apr 3 2015
    Event12th European Signal Processing Conference, EUSIPCO 2004 - Vienna, Austria
    Duration: Sep 6 2004Sep 10 2004

    Publication series

    NameEuropean Signal Processing Conference
    Volume06-10-September-2004
    ISSN (Print)2219-5491

    Other

    Other12th European Signal Processing Conference, EUSIPCO 2004
    CountryAustria
    CityVienna
    Period9/6/049/10/04

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Electrical and Electronic Engineering

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