• DocumentCode
    254343
  • Title

    SphereFlow: 6 DoF Scene Flow from RGB-D Pairs

  • Author

    Hornacek, Michael ; Fitzgibbon, Andrew ; Rother, Carsten

  • Author_Institution
    Tech. Univ. Vienna, Vienna, Austria
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    3526
  • Lastpage
    3533
  • Abstract
    We take a new approach to computing dense scene flow between a pair of consecutive RGB-D frames. We exploit the availability of depth data by seeking correspondences with respect to patches specified not as the pixels inside square windows, but as the 3D points that are the inliers of spheres in world space. Our primary contribution is to show that by reasoning in terms of such patches under 6 DoF rigid body motions in 3D, we succeed in obtaining compelling results at displacements large and small without relying on either of two simplifying assumptions that pervade much of the earlier literature: brightness constancy or local surface planarity. As a consequence of our approach, our output is a dense field of 3D rigid body motions, in contrast to the 3D translations that are the norm in scene flow. Reasoning in our manner additionally allows us to carry out occlusion handling using a 6 DoF consistency check for the flow computed in both directions and a patchwise silhouette check to help reason about alignments in occlusion areas, and to promote smoothness of the flow fields using an intuitive local rigidity prior. We carry out our optimization in two steps, obtaining a first correspondence field using an adaptation of PatchMatch, and subsequently using alpha-expansion to jointly handle occlusions and perform regularization. We show attractive flow results on challenging synthetic and real-world scenes that push the practical limits of the aforementioned assumptions.
  • Keywords
    image sequences; natural scenes; optimisation; 3D points; 3D rigid body motions; 3D translations; 6 DoF consistency checkfor; 6 DoF rigid body motions; 6 DoF scene flow; PatchMatch; RGB-D pairs; SphereFlow; brightness constancy; consecutive RGB-D frames; dense scene flow; depth data availability; intuitive local rigidity prior; local surface planarity; occlusion areas; optimization; patchwise silhouette check; Brightness; Cameras; Cognition; Geometry; Solid modeling; Three-dimensional displays; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.451
  • Filename
    6909846