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Proceedings Paper

Relaxation method for segmenting quadratic surfaces from depth and intensity images
Author(s): Gunasekaran Seetharaman; Henry C. Chu; Syed Shafiullah
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Paper Abstract

Recovery of shape and structure of objects present in a scene from its image is a significant problem in vision. The purpose of this paper is to develop and demonstrate an iterative relaxation algorithm that combines (by a fusion process) surface interpolation using a nonuniformly sampled range image and the recovery of shape from shading of a uniformly sampled intensity image. The recovery of shape from shading requires uniform lighting, as well as uniform viewing directions across the scene which is difficult to achieve. The objective is to extract several piecewise planar surfaces whose orientation parameters are extracted iteratively. With a few exceptions, most range sensors provide nonuniformly sampled depth images. It is desirable to extract the intrinsic surfaces and resample the image over a uniformly spaced grid. Then, it is expected that the structure of each image is isomorphic to that of the other image. Once the structure based region/volume correspondence is established, it becomes possible to adapt the consistency constraint for each surface and the smoothness criterion at the boundaries between two surfaces, and to activate resegmentation (incremental) if necessary.

Paper Details

Date Published: 1 March 1992
PDF: 7 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58567
Show Author Affiliations
Gunasekaran Seetharaman, Univ. of Southwestern Louisiana (United States)
Henry C. Chu, Univ. of Southwestern Louisiana (United States)
Syed Shafiullah, Univ. of Southwestern Louisiana (United States)

Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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