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    Combined Stochastic-Deterministic Solution for Tracking Multiple Objects with an Stereo-Vision System

    TitleCombined Stochastic-Deterministic Solution for Tracking Multiple Objects with an Stereo-Vision System
    Publication TypeJournal Article
    Año de publicación2006
    AutoresMarron, M, Sotelo, MA, Garcia, JC
    Idioma de publicaciónEnglish
    JournalWSEAS Transactions on Signal Processing
    Volumen2
    Número2
    Páginas253-260
    Fecha de publicación02/2006
    Palabras clavebayesian estimation, Multi-Object Tracking, multimodal probability distribution, Particle Filters, visual tracking
    ISSN1790-502
    Abstract

    In this paper, the authors propose the use of a probabilistic algorithm to develop a multi-object tracking task. Different solutions have already been proposed by the scientific community to find a solution for this application, and the particle filter is proven to be the best choice in this case as the multimodality character of this Bayes filter implementation can be well-spent: an only particle filter can be used to track a variable number of objects. On the other hand, the flexibility of the particle filter can become in a lack of robustness for the estimator, so a deterministic algorithm is added to the standard filter to increase it. In the following paragraphs the global combined algorithm is described and different tests based on stereo-vision information are also included, proving the reliability of the proposal tracker

    Resumen

    In this paper, the authors propose the use of a probabilistic algorithm to develop a multi-object tracking task. Different solutions have already been proposed by the scientific community to find a solution for this application, and the particle filter is proven to be the best choice in this case as the multimodality character of this Bayes filter implementation can be well-spent: an only particle filter can be used to track a variable number of objects. On the other hand, the flexibility of the particle filter can become in a lack of robustness for the estimator, so a deterministic algorithm is added to the standard filter to increase it. In the following paragraphs the global combined algorithm is described and different tests based on stereo-vision information are also included, proving the reliability of the proposal tracker

    AttachmentSize
    journal3.pdf1.49 MB