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Proceedings Paper

Interpolation Of Stereo Data With Shepard' S Surfaces
Author(s): R. Srinivasan; M. Shridhar; M. Ahmadi
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Paper Abstract

Scene analysis requires surface information in the form of depth to be computed at all points in the image. Of the several cues available to compute depth, the retinal disparity has been proven to be the most reliable one and hence numerous stereo algorithms have been reported. A class of these algorithms, known as feature based, computes the disparity only at the edge locations in the image. Because we need depth at all the points in the image, this scarce data has to be used to estimate depth at all points in the image. While this problem could be posed as a multivariate minimization problem as Grimson suggested, the weighted sum scheme proposed by Shepard to interpolate scarce data in the geophysical domain seems to be a more computationally affordable scheme. A few interesting niceties of this scheme are: (i) the analyticity of the interpolant everywhere except at the vicinity of the data points but its mere continuousness at the data points (not even differentiable once), (ii) its similarity to the familiar gravitational models and (iii) its elegant biological feasibility. In addition, the derivative information obtained from other cues such as shading can be gracefully combined to present a unified percept of surface information. In this paper we discuss about the use of local version of this scheme to interpolate the stereo data.

Paper Details

Date Published: 19 February 1988
PDF: 9 pages
Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); doi: 10.1117/12.942772
Show Author Affiliations
R. Srinivasan, University of Windsor (Canada.)
M. Shridhar, University of Michigan-Dearborn (United States)
M. Ahmadi, University of Windsor (Canada)


Published in SPIE Proceedings Vol. 0848:
Intelligent Robots and Computer Vision VI
David P. Casasent; Ernest L. Hall, Editor(s)

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