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Fast digital optical flow estimation based on EMD

Conference Paper


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Abstract


  • This paper presents an optical flow estimation technique based on the so called Elementary Motion Detector (EMD). The aim is to provide a fast but not necessarily very accurate system to be used for specific post processing purposes. This model uses a low complexity algorithm for detecting motion in four directions by identifying specific motion templates. By extending the motion templates to different scales of the input video, an Elementary Velocity Detector (EVD) is created. This one can save computation time by estimating different speeds in parallel. Information from the EVD outputs is then used to generate an estimate of the optical flow along edges and other intensity transitions. Experimen-

    tal results are presented, which show the effectiveness of the proposed model. Furthermore, the robustness of the model can be enhanced by using pre-filtering.

Publication Date


  • 2010

Citation


  • Quelin, M., Bouzerdoum, A. & Phung, S. (2010). Fast digital optical flow estimation based on EMD. European Workshop on Visual Information Processing (pp. 155-158). USA: IEEE.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1823&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/812

Start Page


  • 155

End Page


  • 158

Abstract


  • This paper presents an optical flow estimation technique based on the so called Elementary Motion Detector (EMD). The aim is to provide a fast but not necessarily very accurate system to be used for specific post processing purposes. This model uses a low complexity algorithm for detecting motion in four directions by identifying specific motion templates. By extending the motion templates to different scales of the input video, an Elementary Velocity Detector (EVD) is created. This one can save computation time by estimating different speeds in parallel. Information from the EVD outputs is then used to generate an estimate of the optical flow along edges and other intensity transitions. Experimen-

    tal results are presented, which show the effectiveness of the proposed model. Furthermore, the robustness of the model can be enhanced by using pre-filtering.

Publication Date


  • 2010

Citation


  • Quelin, M., Bouzerdoum, A. & Phung, S. (2010). Fast digital optical flow estimation based on EMD. European Workshop on Visual Information Processing (pp. 155-158). USA: IEEE.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1823&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/812

Start Page


  • 155

End Page


  • 158