An Experimental Comparison of Range Image Segmentation Algorithms

  • Authors:
  • Adam Hoover;Gillian Jean-Baptiste;Xiaoyi Jiang;Patrick J. Flynn;Horst Bunke;Dmitry B. Goldgof;Kevin Bowyer;David W. Eggert;Andrew Fitzgibbon;Robert B. Fisher

  • Affiliations:
  • -;-;-;-;-;-;-;-;-;-

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 1996

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Abstract

A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves 1) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and 2) a set of defined performance metrics for instances of correctly segmented, missed, and noise regions, over- and under-segmentation, and accuracy of the recovered geometry. A tool is used to objectively compare a machine generated segmentation against the specified ground truth. Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches.