• DocumentCode
    2712690
  • Title

    Automated reconstruction of tree structures using path classifiers and Mixed Integer Programming

  • Author

    Türetken, Engin ; Benmansour, Fethallah ; Fua, Pascal

  • Author_Institution
    Comput. Vision Lab. (EPFL), Lausanne, Switzerland
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    566
  • Lastpage
    573
  • Abstract
    Although tracing linear structures in 2D images and 3D image stacks has received much attention over the years, full automation remains elusive. In this paper, we formulate the delineation problem as one of solving a Quadratic Mixed Integer Program (Q-MIP) in a graph of potential paths, which can be done optimally up to a very small tolerance. We further propose a novel approach to weighting these paths, which results in a Q-MIP solution that accurately matches the ground truth. We demonstrate that our approach outperforms a state-of-the-art technique based on the k-Minimum Spanning Tree formulation on a 2D dataset of aerial images and a 3D dataset of confocal microscopy stacks.
  • Keywords
    graph theory; image reconstruction; integer programming; tree data structures; 2D images; 3D image stacks; Q-MIP; aerial images; automated reconstruction; confocal microscopy stacks; delineation problem; graph theory; k-minimum spanning tree; linear structures; mixed integer programming; path classifiers; potential paths; quadratic mixed integer program; tree structures; Histograms; Image edge detection; Image reconstruction; Joining processes; Noise; Robustness; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247722
  • Filename
    6247722