Surface segmentation of laser range images for automated facility mapping

Ralph J. Pinheiro; Carl D. Crane III; James S. Tulenko; Dean Haddox

doi:10.1117/12.257255

31 October 1996 Surface segmentation of laser range images for automated facility mapping

Ralph J. Pinheiro, Carl D. Crane III, James S. Tulenko, Dean Haddox

Proceedings Volume 2908, Machine Vision Applications, Architectures, and Systems Integration V; (1996) https://doi.org/10.1117/12.257255
Event: Photonics East '96, 1996, Boston, MA, United States

Abstract

A method for modeling a hazardous environment automatically, for real time task planning, using laser range images of multiple partial views of a single work space scene, is presented. Viewpoint invariant properties of differential- geometric shape descriptors like the mean curvature and the Gaussian curvature are utilized to classify a pre-smoothed laser range image into one of eight basic surface types. Connected components of these classified pixels, that satisfy specific planarity constraints, are clustered into planar regions. Selected image processing techniques are applied to the planar regions in order to extract their critical features, and to synthesize those polygons, with normals approximately orthogonal to the sensor view-axis. Detailed shape of the objects in the scene develop through view integration of multiple partial views of the objects in the scene.

Citation Download Citation

Ralph J. Pinheiro, Carl D. Crane III, James S. Tulenko, and Dean Haddox "Surface segmentation of laser range images for automated facility mapping", Proc. SPIE 2908, Machine Vision Applications, Architectures, and Systems Integration V, (31 October 1996); https://doi.org/10.1117/12.257255

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