An experimental comparison of range image segmentation algorithms
Adam W. Hoover, Guertson Jean-Baptiste, Xiaoyi Jiang, Patrick J. Flynn, Horst Bunke, Dmitry B. Goldgof, Kevin W. Bowyer, Daniel Eggert, Andrew W Fitzgibbon, Robert Bob Fisher · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1996
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.