Real-time range image segmentation using adaptive kernels and Kalman filtering

Author

DePiero, E.W. ; Trivedi, M.M.

Author_Institution

EE Dept., California Polytech. State Univ., San Luis Obispo, CA, USA

Volume

3

fYear

1996

fDate

25-29 Aug 1996

Firstpage

573

Abstract

Segmentation is a fundamental process affecting the overall quality and utility of a machine vision system. Range profile tracking (RPT) is a systematic approach for stable, accurate and high speed segmentation of range images that is based on Kalman filtering. Tests of RPT have produced stable decompositions of second order surfaces bounded by jump and crease discontinuities, having a volumetric error of a few percent, in under 6 sec. for a wide variety of conditions. Results from over 900 tests on synthetic scenes and 150 real range images are presented

Keywords

Kalman filters; computer vision; filtering theory; image segmentation; Kalman filtering; adaptive kernels; crease discontinuities; jump discontinuities; machine vision system; range profile tracking; real-time range image segmentation; second order surfaces; stable decompositions; volumetric error; Adaptive filters; Filtering; Image analysis; Image segmentation; Kalman filters; Kernel; Layout; Machine vision; Strips; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.547012

Filename

547012