An experimental comparison of range image segmentation algorithms

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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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 1996-07, Vol.18 (7), p.673-689
Hauptverfasser: 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: Artikel
Sprache:eng
Schlagworte:
Artificial intelligence
Computer vision
Geometrical optics
Geometry
Image segmentation
Laser noise
Measurement standards
Pixel
Shape
Testing
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Beschreibung
Zusammenfassung: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.
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/34.506791