• DocumentCode
    161030
  • Title

    Robust depth estimation with occlusion detection using concepts of optical flow

  • Author

    Raveshiya, Hiral ; Sanghavi, Ankita

  • Author_Institution
    Comput. Eng. Dept., Vidya Vikas Educ. Trust´s Universal Coll. Of Eng., Thane, India
  • fYear
    2014
  • fDate
    4-5 April 2014
  • Firstpage
    327
  • Lastpage
    331
  • Abstract
    In this paper we present an approach to go beyond the accuracy limits of current optical flow estimators. We have used coarse to over-fine approach along with hybrid interpolation to upgrade coarse to fine approach. Coarse to fine approach is used by most modern optical flow algorithms. Results of suggested method show benefit for sub-pixel motion. It also reduces the estimation error to great extent. Hybrid interpolation method is used which is an integration of bilinear and bi-cubic interpolation methods. Results of our approach on benchmark sequences show that estimated depth map are clearer and boundaries are sharper than original coarse to fine approach with bi-cubic interpolation method. Once optical flow vectors are found occlusion is detected based on the concept of residual error image.
  • Keywords
    image motion analysis; image sequences; interpolation; object detection; benchmark sequences; bi-cubic interpolation methods; bilinear interpolation methods; estimated depth map; estimation error reduction; hybrid interpolation method; occlusion detection; optical flow estimators; optical flow vectors; residual error image; robust depth estimation; sub-pixel motion; Adaptive optics; Computer vision; Estimation; Image motion analysis; Interpolation; Optical filters; Optical imaging; Coarse to over-fine optical flow; Hybrid interpolation; Occlusion; Optical Flow; Residual error image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits, Systems, Communication and Information Technology Applications (CSCITA), 2014 International Conference on
  • Conference_Location
    Mumbai
  • Type

    conf

  • DOI
    10.1109/CSCITA.2014.6839281
  • Filename
    6839281