An experimental comparison of range image segmentation algorithms

Author

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.

Author_Institution

Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA

Volume

18

Issue

7

fYear

1996

fDate

7/1/1996 12:00:00 AM

Firstpage

673

Lastpage

689

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.

Keywords

image classification; image segmentation; laser ranging; laser range finder images; over-segmentation; performance metrics; planar patches; range image segmentation algorithms; recovered geometry; structured light scanner images; under-segmentation; Artificial intelligence; Computer vision; Geometrical optics; Geometry; Image segmentation; Laser noise; Measurement standards; Pixel; Shape; Testing;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.506791

Filename

506791