PSO-particle filter-based biometric measurement for human tracking

Zhenyuan Xu, Junzo Watada

    Research output: Contribution to journalArticle

    Abstract

    Today, security and surveillance systems are required not only to track the motions of humans but also, in some situations, to recognize and measure biometric features such as width and length. Few methods have been proposed for biometric height measurement in human tracking. Some studies have shown that an infrared ray technique can survey the height of a human, but the equipment required is complicated. The objective of this paper is to build a mathematical model to measure the biometrics of human tracking. This tracking method can show humans' and objects' size in a picture so that, if we put this picture in a frame of axes, we can calculate the height and other biometric lengths. To obtain the most accurate results for biometric length surveillance, we need a tracking methodthat is more exact than conventional tracking results. Combining tracking and detection methods using a particle swarm optimization-particle filter shows results with great accuracy in human tracking.

    Original languageEnglish
    Pages (from-to)533-539
    Number of pages7
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume16
    Issue number4
    Publication statusPublished - 2012 Jun

    Fingerprint

    Biometrics
    Particle swarm optimization (PSO)
    Mathematical models
    Infrared radiation

    Keywords

    • Accuracy
    • Height surveying
    • Human tracking
    • Particle filter

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

    Cite this

    PSO-particle filter-based biometric measurement for human tracking. / Xu, Zhenyuan; Watada, Junzo.

    In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 16, No. 4, 06.2012, p. 533-539.

    Research output: Contribution to journalArticle

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