• DocumentCode
    1646631
  • Title

    Multi-view support vector machines for distributed activity recognition

  • Author

    Mosabbeb, Ehsan Adeli ; Raahemifar, Kaamran ; Fathy, Mahmood

  • Author_Institution
    Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2013
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    In this paper, we propose a Multi-view Distributed SVM model. Most distributed classification models, distribute the instances among their processing nodes, while we assume that one instance is formed as a combination of information from different sources. This makes our model a great choice for multi-view activity recognition in camera sensor networks. We demonstrate the effectiveness of the algorithm, using the IXMAS dataset.
  • Keywords
    computer vision; image classification; object recognition; support vector machines; IXMAS dataset; camera sensor network; distributed activity recognition; distributed classification model; multiview activity recognition; multiview distributed SVM model; multiview support vector machine; Accuracy; Support vector machines; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Smart Cameras (ICDSC), 2013 Seventh International Conference on
  • Conference_Location
    Palm Springs, CA
  • Type

    conf

  • DOI
    10.1109/ICDSC.2013.6778240
  • Filename
    6778240