• Stud Health Technol Inform · Jan 2013

    Video segmentation of moving humans for assistive environments.

    • Ilias Maglogiannis, K K Delibasis, T Goudas, Andriana Prentza, Flora Malamateniou, and George Vassilacopoulos.
    • Department of Digital Systems, University of Piraeus, Greece.
    • Stud Health Technol Inform. 2013 Jan 1; 190: 179-82.

    AbstractIn this paper, we present two recently proposed efficient methods for human segmentation from video in indoor environments: the illumination sensitive background method and the self-organizing background subtraction (SOBS) method. Both methods maintain multiple background models. The SOBS method has been modified in this work for gray-scale frames, in order to decrease processing times. The video data are acquired indoors from a fixed fish-eye camera in the living environment. The paper presents the algorithmic implementation and modifications details, while results are also presented for a small number of video sequences.

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