• DocumentCode
    2340293
  • Title

    Classifying bags of keypoints using HMMs

  • Author

    Zaklouta, Fatin ; Stanciulescu, Bogdan

  • Author_Institution
    Mines ParisTech, Paris, France
  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    In this paper, we use a Hidden Markov Models (HMM) to classify bags of SURF keypoints descriptors of a given class. The performance of this technique is compared to that of others, by testing it on various multi-class datasets. We also describe a prospective of expanding our application to include the detection and classification of moving objects in a video stream using optical flow and Self Organizing Maps (SOM).
  • Keywords
    hidden Markov models; image classification; video streaming; HMM; SURF bag; hidden markov model; moving objects classification; moving objects detection; multiclass dataset; optical flow; self organizing map; video stream; Accuracy; Feature extraction; Hidden Markov models; Kernel; Robustness; Streaming media; Training; Hidden Markov Models; Multi-class; SURF; bag of features; classification; keypoints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2010 IEEE/ACS International Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4244-7716-6
  • Type

    conf

  • DOI
    10.1109/AICCSA.2010.5587039
  • Filename
    5587039
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2340293