Person identification from actions based on dynemes and discriminant learning

Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas

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

    4 Citations (Scopus)

    Abstract

    In this paper we present a view-independent person identification method exploiting motion information. A multi-camera setup is used in order to capture the human body during action execution from different viewing angles. The method is able to incorporate several everyday actions in person identification. A comparative study of the discriminative ability of different actions for person identification is provided, denoting that several actions, except walk, can be exploited for person identification.

    Original languageEnglish
    Title of host publication2013 International Workshop on Biometrics and Forensics, IWBF 2013
    DOIs
    Publication statusPublished - 2013
    Publication typeA4 Article in conference proceedings
    Event1st International Workshop on Biometrics and Forensics, IWBF 2013 - Lisbon, Portugal
    Duration: 4 Apr 20135 Apr 2013

    Conference

    Conference1st International Workshop on Biometrics and Forensics, IWBF 2013
    Country/TerritoryPortugal
    CityLisbon
    Period4/04/135/04/13

    Keywords

    • Action-based person identification
    • Classification results fusion
    • Discriminant learning
    • Dyneme video representation

    ASJC Scopus subject areas

    • Biotechnology
    • Computer Science Applications

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