• DocumentCode
    248395
  • Title

    Optical Flow Motion Detection on Raspberry Pi

  • Author

    Baby, Rinu Merin ; Ahamed, Rooha Razmid

  • Author_Institution
    Electron. & Commun. Dept., RSET, Kochi, India
  • fYear
    2014
  • fDate
    27-29 Aug. 2014
  • Firstpage
    151
  • Lastpage
    152
  • Abstract
    This paper presents the implementation of Optical Flow Motion Detection algorithm on Raspberry Pi. The Lucas-Kanade method was chosen for the implementation. The algorithm works by comparing two successive image frames. To find out a displaced object, the algorithm tries to guess the direction of displaced object rather than scanning the second image for the matching pixel. This can be done by solving for the optical flow vector by assuming that the vector will be similar to a small neighbourhood surrounding the pixel. The algorithm was simulated using Python OpenCV. The implementation of Lucas-Kanade algorithm was successfully done on Raspberry Pi.
  • Keywords
    image matching; image motion analysis; image sequences; vectors; Lucas-Kanade method; Python OpenCV; Raspberry Pi; image frames; image matching; optical flow motion detection; optical flow vector; Adaptive optics; Integrated optics; Motion detection; Optical imaging; Optical sensors; Streaming media; Vectors; Lucas-Kanade; motion detection; optical flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computing and Communications (ICACC), 2014 Fourth International Conference on
  • Conference_Location
    Cochin
  • Print_ISBN
    978-1-4799-4364-7
  • Type

    conf

  • DOI
    10.1109/ICACC.2014.42
  • Filename
    6906011