An experimental comparison of range image segmentation algorithms

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 corr...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence Vol. 18; no. 7; pp. 673 - 689
Main Authors: Hoover, A., Jean-Baptiste, G., Jiang, X., Flynn, P.J., Bunke, H., Goldgof, D.B., Bowyer, K., Eggert, D.W., Fitzgibbon, A., Fisher, R.B.
Format: Journal Article
Language:English
Published: IEEE 01.07.1996
Subjects:
Artificial intelligence
Computer vision
Geometrical optics
Geometry
Image segmentation
Laser noise
Measurement standards
Pixel
Shape
Testing
ISSN:0162-8828, 2160-9292
Online Access:Get full text
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Summary: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.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0162-8828
2160-9292
DOI:10.1109/34.506791