• DocumentCode
    1732305
  • Title

    Detection of independently moving objects in passive video

  • Author

    Morimoto, Carlos ; DeMenthon, Daniel ; Davis, Larry ; Chellappa, Rama ; Nelson, Randal

  • Author_Institution
    Comput. Vision Lab., Maryland Univ., College Park, MD, USA
  • fYear
    1995
  • Firstpage
    270
  • Lastpage
    275
  • Abstract
    We present two different approaches for the identification of independently moving objects (IMOs) and demonstrate their application to outdoor imagery taken from a moving autonomous vehicle. Both approaches involve image stabilization followed by an analysis of the stabilized image sequence. The stabilization reduces the effects of the movement of the autonomous vehicle, facilitating the detection of the IMOs. In the first approach, IMOs are detected based on a filtering approach that integrates the results of velocity tuned filters over several frames. In the second approach IMOs are identified by constraints on allowable values of the optic flow field after stabilization
  • Keywords
    computer vision; filtering theory; image sequences; object detection; object recognition; real-time systems; road traffic; traffic control; filtering; image sequence; image stabilization; independently moving object detection; moving autonomous vehicle; optic flow field; outdoor imagery; passive video; Filtering; Image analysis; Image motion analysis; Image sequence analysis; Image sequences; Mobile robots; Object detection; Optical filters; Remotely operated vehicles; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles '95 Symposium., Proceedings of the
  • Conference_Location
    Detroit, MI
  • Print_ISBN
    0-7803-2983-X
  • Type

    conf

  • DOI
    10.1109/IVS.1995.528292
  • Filename
    528292