• DocumentCode
    597922
  • Title

    Toward a real-time tracking of dense point-sampled geometry

  • Author

    Destelle, Francois ; Roudet, C. ; Neveu, M. ; Dipanda, Albert

  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    381
  • Lastpage
    384
  • Abstract
    In this paper, we address the problem of tracking temporal deformations between two arbitrary densely sampled point-based surfaces. We propose an intuitive and efficient resolution to the point matching problem within two frames of a sequence. The proposed method utilizes two distinct space partition trees, one for each point cloud, which both are defined on a unique discrete space. Our method takes advantage of multi-resolution concerns, voxel adjacency relations, and a specific distance function. Experimental results obtained from both simulated and real reconstructed data sets demonstrate that the proposed method can handle efficiently the tracking process even for very large point clouds. Moreover, our method is easy to implement and very fast, which provides possibilities for real-time tracking applications.
  • Keywords
    computer graphics; geometry; image matching; image reconstruction; image resolution; object tracking; real-time systems; trees (mathematics); arbitrary densely sampled point-based surfaces; dense point-sampled geometry; discrete space; distance function; efficient resolution; intuitive resolution; multiresolution concerns; point clouds; point matching problem; real reconstructed data sets; real-time tracking; simulated reconstructed data sets; space partition trees; temporal deformations tracking; tracking process; voxel adjacency relations; Heuristic algorithms; Octrees; Partitioning algorithms; Real-time systems; Shape; Tracking; Vectors; 3D Processing; Computer Vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6466875
  • Filename
    6466875