Type-2 Fuzzy Mixture of Gaussians Model: Application to Background Modeling View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2008

AUTHORS

Fida El Baf , Thierry Bouwmans , Bertrand Vachon

ABSTRACT

Background modeling is a key step of background subtraction methods used in the context of static camera. The goal is to obtain a clean background and then detect moving objects by comparing it with the current frame. Mixture of Gaussians Model [1] is the most popular technique and presents some limitations when dynamic changes occur in the scene like camera jitter, illumination changes and movement in the background. Furthermore, the MGM is initialized using a training sequence which may be noisy and/or insufficient to model correctly the background. All these critical situations generate false classification in the foreground detection mask due to the related uncertainty. To take into account this uncertainty, we propose to use a Type-2 Fuzzy Mixture of Gaussians Model. Results show the relevance of the proposed approach in presence of camera jitter, waving trees and water rippling. More... »

PAGES

772-781

References to SciGraph publications

  • 2003-07. Human Body Model Acquisition and Tracking Using Voxel Data in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2000. Non-parametric Model for Background Subtraction in COMPUTER VISION — ECCV 2000
  • 2005-12. Robust Background Subtraction with Foreground Validation for Urban Traffic Video in APPLIED SIGNAL PROCESSING
  • 2005. A Kalman Filter Based Background Updating Algorithm Robust to Sharp Illumination Changes in IMAGE ANALYSIS AND PROCESSING – ICIAP 2005
  • 1995-05. Segmentation and tracking of piglets in images in MACHINE VISION AND APPLICATIONS
  • Book

    TITLE

    Advances in Visual Computing

    ISBN

    978-3-540-89638-8
    978-3-540-89639-5

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-89639-5_74

    DOI

    http://dx.doi.org/10.1007/978-3-540-89639-5_74

    DIMENSIONS

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