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Proceedings Paper

Hierarchical fusion of geometric constraints for image segmentation
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Paper Abstract

Segmentation of range and intensity image pair of a 3-D scene for model based 3-D object recognition is considered. Hierarchical algorithms exist for segmenting each image individually. We emphasize the degree of similarity in the computation at each level of the hierarchy and note that, in some cases, at the intermediate levels of abstraction (such as local-shape from shading) the uncertainties that exist in range and intensity images are of complementary nature. Certain geometric and surface constraints are illustrated to have such property. A multistage segmentation approach that follows a hierarchical computation in lock-step is then developed. The possibility of parallelizing the computation at different levels is also examined.

Paper Details

Date Published: 1 April 1991
PDF: 7 pages
Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25298
Show Author Affiliations
Gunasekaran Seetharaman, Univ. of Southwestern Louisiana (United States)
Chee-Hung Henry Chu, Univ. of Southwestern Louisiana (United States)


Published in SPIE Proceedings Vol. 1383:
Sensor Fusion III: 3D Perception and Recognition
Paul S. Schenker, Editor(s)

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