Lancaster EPrints

Video foreground detection based on symmetric alpha-stable mixture models.

Bhaskar, H. and Mihaylova, Lyudmila and Achim, A. (2010) Video foreground detection based on symmetric alpha-stable mixture models. IEEE Transactions on Circuits and Systems for Video Technology, 20 (8). pp. 1133-1138. ISSN 1051-8215

[img]
Preview
PDF (SAS_BS_in_press.pdf)
Download (997Kb) | Preview

    Abstract

    Background subtraction (BS) is an efficient technique for detecting moving objects in video sequences. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. These assumptions restrict the applicability of BS methods to real-time object detection in video. In this paper, we propose an extended cluster BS technique with a mixture of symmetric alpha stable (SS) distributions. An on-line self-adaptive mechanism is presented that allows automated estimation of the model parameters using the log moment method. Results over real video sequences from indoor and outdoor environments, with data from static and moving video cameras are presented. The SS mixture model is shown to improve the detection performance compared with a cluster BS method using a Gaussian mixture model and the method of Li et al. [11].

    Item Type: Article
    Journal or Publication Title: IEEE Transactions on Circuits and Systems for Video Technology
    Additional Information: "©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE." "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder."
    Uncontrolled Keywords: automatic object detection ; background subtraction ; segmentation ; alpha stable distribution
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Departments: Faculty of Science and Technology > School of Computing & Communications
    ID Code: 32893
    Deposited By: Dr L Mihaylov
    Deposited On: 26 Apr 2010 09:57
    Refereed?: Yes
    Published?: Published
    Last Modified: 23 Sep 2013 15:49
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/32893

    Actions (login required)

    View Item